{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "2023-03-08 19:31:12.394118: I tensorflow/core/platform/cpu_feature_guard.cc:193] This TensorFlow binary is optimized with oneAPI Deep Neural Network Library (oneDNN) to use the following CPU instructions in performance-critical operations:  AVX2 AVX512F AVX512_VNNI FMA\n",
      "To enable them in other operations, rebuild TensorFlow with the appropriate compiler flags.\n",
      "2023-03-08 19:31:12.536508: I tensorflow/core/util/port.cc:104] oneDNN custom operations are on. You may see slightly different numerical results due to floating-point round-off errors from different computation orders. To turn them off, set the environment variable `TF_ENABLE_ONEDNN_OPTS=0`.\n",
      "2023-03-08 19:31:13.116301: W tensorflow/compiler/xla/stream_executor/platform/default/dso_loader.cc:64] Could not load dynamic library 'libnvinfer.so.7'; dlerror: libnvinfer.so.7: cannot open shared object file: No such file or directory; LD_LIBRARY_PATH: :/home/ubuntu/data/miniconda3/envs/tf2/lib/\n",
      "2023-03-08 19:31:13.116401: W tensorflow/compiler/xla/stream_executor/platform/default/dso_loader.cc:64] Could not load dynamic library 'libnvinfer_plugin.so.7'; dlerror: libnvinfer_plugin.so.7: cannot open shared object file: No such file or directory; LD_LIBRARY_PATH: :/home/ubuntu/data/miniconda3/envs/tf2/lib/\n",
      "2023-03-08 19:31:13.116409: W tensorflow/compiler/tf2tensorrt/utils/py_utils.cc:38] TF-TRT Warning: Cannot dlopen some TensorRT libraries. If you would like to use Nvidia GPU with TensorRT, please make sure the missing libraries mentioned above are installed properly.\n"
     ]
    }
   ],
   "source": [
    "import numpy as np\n",
    "import tensorflow as tf\n",
    "import tensorflow_compression as tfc\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "import os\n",
    "import h5py\n",
    "\n",
    "from BalleFFP_improved import BalleFFP\n",
    "from read_data import read_data_numpy"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## General Settings"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "from tensorflow.python.ops.numpy_ops import np_config\n",
    "np_config.enable_numpy_behavior()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "plt.rcParams[\"font.family\"] = \"serif\"\n",
    "plt.rcParams[\"font.size\"]   = 14"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "2023-03-08 19:31:20.495834: I tensorflow/compiler/xla/stream_executor/cuda/cuda_gpu_executor.cc:981] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero\n",
      "2023-03-08 19:31:20.497323: I tensorflow/compiler/xla/stream_executor/cuda/cuda_gpu_executor.cc:981] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero\n",
      "2023-03-08 19:31:20.509282: I tensorflow/compiler/xla/stream_executor/cuda/cuda_gpu_executor.cc:981] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero\n",
      "2023-03-08 19:31:20.510926: I tensorflow/compiler/xla/stream_executor/cuda/cuda_gpu_executor.cc:981] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero\n",
      "2023-03-08 19:31:20.512205: I tensorflow/compiler/xla/stream_executor/cuda/cuda_gpu_executor.cc:981] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero\n",
      "2023-03-08 19:31:20.513471: I tensorflow/compiler/xla/stream_executor/cuda/cuda_gpu_executor.cc:981] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero\n"
     ]
    }
   ],
   "source": [
    "tf.config.set_visible_devices([], 'GPU')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Functions"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "def get_model_files(folder, *keys):\n",
    "    files  = os.listdir(folder)\n",
    "    for key in keys:\n",
    "        files  = [f for f in files if key in f]\n",
    "    models = [f for f in files if \"model\" in f]\n",
    "    losses = [f for f in files if \"losses\" in f]\n",
    "    return models, losses"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "def show_image_comparison(img, reco, id, format):\n",
    "    \"\"\"Visualize the original image and the reconstructed image side by side.\"\"\"\n",
    "    if format=='channels_first':\n",
    "        img  = np.transpose(img, (1, 2, 0))\n",
    "        reco = np.transpose(reco, (1, 2, 0))\n",
    "    \n",
    "    # check if the images are normalized\n",
    "    norm_img  = np.max(img)  <= 1.0\n",
    "    norm_reco = np.max(reco) <= 1.0\n",
    "\n",
    "    # Create a 4x4 grid of images\n",
    "    fig, axes = plt.subplots(nrows=1, ncols=2, figsize=(14, 7), constrained_layout=True)\n",
    "    axes[0].imshow(img  if norm_img  else img.astype(np.uint8)) \n",
    "    axes[1].imshow(reco if norm_reco else reco.astype(np.uint8)) \n",
    "    \n",
    "    axes[0].axis('off')\n",
    "    axes[1].axis('off')\n",
    "    \n",
    "    fig.suptitle('Original image (left) and reconstructed image (right) (id: {})'.format(id))\n",
    "\n",
    "    # Show the plot\n",
    "    plt.show()\n",
    "\n",
    "def show_image_comparison_bitrate(img, reco, id, format, compressor):\n",
    "    \"\"\"Visualize the original image and the reconstructed image side by side.\"\"\"\n",
    "    if format=='channels_first':\n",
    "        img  = np.transpose(img, (1, 2, 0))\n",
    "        reco = np.transpose(reco, (1, 2, 0))\n",
    "    \n",
    "    # check if the images are normalized\n",
    "    norm_img  = np.max(img)  <= 1.0\n",
    "    norm_reco = np.max(reco) <= 1.0\n",
    "\n",
    "    bits_img     = np.product(img.shape)*8\n",
    "    _, bits_reco = compressor(np.expand_dims(img, 0))\n",
    "\n",
    "    print('Bitrate shape:', bits_reco.shape)\n",
    "\n",
    "    # Create a 4x4 grid of images\n",
    "    fig, axes = plt.subplots(nrows=1, ncols=2, figsize=(14, 7), constrained_layout=True)\n",
    "    axes[0].imshow(img  if norm_img  else img.astype(np.uint8)) \n",
    "    axes[1].imshow(reco if norm_reco else reco.astype(np.uint8)) \n",
    "    \n",
    "    axes[0].axis('off')\n",
    "    axes[1].axis('off')\n",
    "\n",
    "    axes[0].set_title(f'{bits_img} bits')\n",
    "    axes[1].set_title(f'{int(tf.reduce_sum(bits_reco))} bits')\n",
    "    \n",
    "    fig.suptitle('Original image (left) and reconstructed image (right) (id: {})'.format(id))\n",
    "\n",
    "    # Show the plot\n",
    "    plt.show()\n",
    "    \n",
    "    return int(tf.reduce_sum(bits_reco))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "def select_random_images(data, n):\n",
    "    \"\"\"Selects n random images from the data.\"\"\"\n",
    "    idx = np.random.choice(data.shape[0], n, replace=False)\n",
    "    return data[idx], idx"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "['#1f77b4', '#ff7f0e', '#2ca02c', '#d62728', '#9467bd', '#8c564b', '#e377c2', '#7f7f7f', '#bcbd22', '#17becf']\n"
     ]
    }
   ],
   "source": [
    "# Get the tab10 colormap from matplotlib\n",
    "tab10 = plt.get_cmap('tab10') # type: ignore\n",
    "\n",
    "# Get the number of colors in the tab10 colormap\n",
    "num_colors = tab10.N\n",
    "\n",
    "# Create a list to store the hex color codes\n",
    "hex_colors = []\n",
    "\n",
    "# Loop through each color in the tab10 colormap and convert it to a hex color code\n",
    "for i in range(num_colors):\n",
    "    rgb_color = tab10(i)[:3]  # Get the RGB values of the color\n",
    "    hex_color = '#{:02x}{:02x}{:02x}'.format(*[int(x * 255) for x in rgb_color])  # Convert the RGB color to a hex color code\n",
    "    hex_colors.append(hex_color)\n",
    "\n",
    "# Print the list of hex color codes\n",
    "print(hex_colors)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "def PSNR(data, normalized = False):\n",
    "\n",
    "    \"\"\"\n",
    "    INPUTS: original image and its compressd version\n",
    "    \"\"\"\n",
    "    mse = tf.reduce_mean((data[0] - data[1]) ** 2)\n",
    "    if(mse == 0):  # MSE is zero means no noise is present in the signal .\n",
    "                  # Therefore PSNR have no importance.\n",
    "        return 10000\n",
    "    if normalized: \n",
    "        max_pixel = 1.0 # if is not normalize\n",
    "    else: \n",
    "        max_pixel = 255.0\n",
    "\n",
    "    psnr = 20 * tf.experimental.numpy.log10(max_pixel / tf.sqrt(mse)) #from definition\n",
    "    return psnr\n",
    "\n",
    "def psnr_onbatch(img, img_reco):\n",
    "\n",
    "    if type(img) == np.ndarray:\n",
    "        img = tf.constant(img)\n",
    "\n",
    "    psnrs       = tf.map_fn(PSNR, (img, img_reco), dtype=(tf.float32, tf.float32), fn_output_signature=tf.float32)\n",
    "    psnr_mean   = tf.reduce_mean(psnrs)\n",
    "    psnr_var    = tf.math.reduce_variance(psnrs)\n",
    "\n",
    "    return psnr_mean.numpy(), tf.sqrt(psnr_var).numpy()\n",
    "\n",
    "\n",
    "def msssim_onbatch(img, img_reco, ch_format, normalized=False):\n",
    "    if ch_format == 'channels_first':\n",
    "        img = img.transpose((0, 2, 3, 1))\n",
    "    if type(img) == np.ndarray:\n",
    "        img = tf.constant(img)\n",
    "\n",
    "    msssim = tf.image.ssim_multiscale(img, img_reco, 1.0 if normalized else 255.0, filter_size=6)\n",
    "    return tf.reduce_mean(msssim).numpy(), tf.sqrt(tf.math.reduce_variance(msssim)).numpy()"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Classes"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [],
   "source": [
    "class Compressor(tf.keras.Model):\n",
    "\n",
    "    def __init__(self, model, cr):\n",
    "\n",
    "        super(Compressor, self).__init__()\n",
    "\n",
    "        self.encoder = model.encoder\n",
    "        self.prior   = model.prior\n",
    "        self.bemodel = tfc.ContinuousBatchedEntropyModel(\n",
    "            prior = self.prior,\n",
    "            coding_rank=cr,\n",
    "            compression=True\n",
    "        )\n",
    "\n",
    "    def call(self, inputs):\n",
    "\n",
    "        encoded = self.encoder(inputs, training=False)\n",
    "\n",
    "        _, bits   = self.bemodel(encoded, training=False)\n",
    "        bitstring = self.bemodel.compress(encoded)\n",
    "\n",
    "        return bitstring, bits\n",
    "    \n",
    "class Decompressor(tf.keras.Model):\n",
    "    def __init__(self, model, cr):\n",
    "\n",
    "        super(Decompressor, self).__init__()\n",
    "\n",
    "        self.encoder = model.encoder\n",
    "        self.prior   = model.prior\n",
    "        self.bemodel = tfc.ContinuousBatchedEntropyModel(\n",
    "            prior = self.prior,\n",
    "            coding_rank=cr,\n",
    "            compression=True\n",
    "        )\n",
    "\n",
    "    def call(self, bitstrings):\n",
    "\n",
    "        decompressed = self.bemodel.decompress(bitstrings, broadcast_shape=[9,9,192])\n",
    "\n",
    "        return decompressed"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Constants"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [],
   "source": [
    "DATA_FOLDER  = \"../data/stl10/stl10_binary/\"\n",
    "DATA_FILE    = \"unlabeled_X.bin\"\n",
    "\n",
    "CH_FORMAT = \"channels_last\"\n",
    "EPOCHS    = 50\n",
    "NORM      = \"normFalse\"\n",
    "COD_RANK  = 3\n",
    "\n",
    "MODEL_FOLDER = \"../models/\""
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Load Data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [],
   "source": [
    "data_path = os.path.join(DATA_FOLDER, DATA_FILE)\n",
    "data      = read_data_numpy(data_path, CH_FORMAT).astype('float32') \n",
    "\n",
    "if NORM == \"normTrue\":\n",
    "    # normalize the data to [0,1]\n",
    "    data = data / 255.0"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Choose the trained model"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "model_ffp_channels_last_epochs50_normFalse_l1e-05_cr3_20230308115252.h5\n",
      "model_ffp_channels_last_epochs50_normFalse_l0.01_cr3_20230308164627.h5\n",
      "model_ffp_channels_last_epochs50_normFalse_l0.0001_cr3_20230308132810.h5\n",
      "model_ffp_channels_last_epochs50_normFalse_l0.001_cr3_20230308150355.h5\n",
      "model_ffp_channels_last_epochs50_normFalse_l0.1_cr3_20230308182410.h5\n",
      "\n",
      "losses_ffp_channels_last_epochs50_normFalse_l0.1_cr3_20230308182410.h5\n",
      "losses_ffp_channels_last_epochs50_normFalse_l1e-05_cr3_20230308115252.h5\n",
      "losses_ffp_channels_last_epochs50_normFalse_l0.001_cr3_20230308150355.h5\n",
      "losses_ffp_channels_last_epochs50_normFalse_l0.0001_cr3_20230308132810.h5\n",
      "losses_ffp_channels_last_epochs50_normFalse_l0.01_cr3_20230308164627.h5\n"
     ]
    }
   ],
   "source": [
    "# name = \"ffp_{}_epochs{}_{}_l{}_cr{}\".format(CH_FORMAT, EPOCHS, NORM, LAMBDA, COD_RANK)\n",
    "cr = f\"cr{COD_RANK}\"\n",
    "date_str = \"202303081\"\n",
    "\n",
    "models, losses = get_model_files(MODEL_FOLDER, cr, date_str)\n",
    "for model in models:\n",
    "    print(model)\n",
    "print()\n",
    "for loss in losses:\n",
    "    print(loss)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[1e-05, 0.01, 0.0001, 0.001, 0.1]\n"
     ]
    }
   ],
   "source": [
    "# from the list of models find the lambda value right after \"l\" and before  the following \"_\"\n",
    "lambdas_from_models = [float(model.split(\"_\")[6].split(\"l\")[1].split(\"_\")[0]) for model in models]\n",
    "print(lambdas_from_models)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[0.1, 1e-05, 0.001, 0.0001, 0.01]\n"
     ]
    }
   ],
   "source": [
    "lambdas_from_losses = [float(loss.split(\"_\")[6].split(\"l\")[1].split(\"_\")[0]) for loss in losses]\n",
    "print(lambdas_from_losses)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[1.e-05 1.e-04 1.e-03 1.e-02 1.e-01]\n",
      "[1.e-05 1.e-04 1.e-03 1.e-02 1.e-01]\n"
     ]
    }
   ],
   "source": [
    "# sort the models and losses according to the lambda values\n",
    "models_sorting = np.argsort(lambdas_from_models)\n",
    "losses_sorting = np.argsort(lambdas_from_losses)\n",
    "print(np.array(lambdas_from_models)[models_sorting])\n",
    "print(np.array(lambdas_from_losses)[losses_sorting])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [],
   "source": [
    "models  = [models[i] for i in models_sorting]\n",
    "losses  = [losses[i] for i in losses_sorting]\n",
    "lambdas = [lambdas_from_models[i] for i in models_sorting]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Loading model from: ../models/model_ffp_channels_last_epochs50_normFalse_l1e-05_cr3_20230308115252.h5\n",
      "Loading model from: ../models/model_ffp_channels_last_epochs50_normFalse_l0.0001_cr3_20230308132810.h5\n",
      "Loading model from: ../models/model_ffp_channels_last_epochs50_normFalse_l0.001_cr3_20230308150355.h5\n",
      "Loading model from: ../models/model_ffp_channels_last_epochs50_normFalse_l0.01_cr3_20230308164627.h5\n",
      "Loading model from: ../models/model_ffp_channels_last_epochs50_normFalse_l0.1_cr3_20230308182410.h5\n"
     ]
    }
   ],
   "source": [
    "models_path = [os.path.join(MODEL_FOLDER, model) for model in models]\n",
    "losses_path = [os.path.join(MODEL_FOLDER, loss)  for loss  in losses]\n",
    "\n",
    "for model_path in models_path:\n",
    "    print(\"Loading model from: {}\".format(model_path))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Train/Test loss"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Loading losses from: ../models/losses_ffp_channels_last_epochs50_normFalse_l1e-05_cr3_20230308115252.h5\n",
      "Loading losses from: ../models/losses_ffp_channels_last_epochs50_normFalse_l0.0001_cr3_20230308132810.h5\n",
      "Loading losses from: ../models/losses_ffp_channels_last_epochs50_normFalse_l0.001_cr3_20230308150355.h5\n",
      "Loading losses from: ../models/losses_ffp_channels_last_epochs50_normFalse_l0.01_cr3_20230308164627.h5\n",
      "Loading losses from: ../models/losses_ffp_channels_last_epochs50_normFalse_l0.1_cr3_20230308182410.h5\n"
     ]
    }
   ],
   "source": [
    "# for every loss file, load them as two numpy arrays train_loss and test_loss\n",
    "train_losses = []   \n",
    "test_losses  = []\n",
    "\n",
    "for loss_path in losses_path:\n",
    "    print(\"Loading losses from: {}\".format(loss_path))\n",
    "    with h5py.File(loss_path, 'r') as f:\n",
    "        train_losses.append(np.array(f['train']))\n",
    "        test_losses.append(np.array(f['test']))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 800x500 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots(figsize=(8, 5), constrained_layout=True)\n",
    "ax.grid(True, which='both', ls='-', lw=0.5, c='grey', alpha=0.3)\n",
    "\n",
    "for i in range(len(train_losses)):\n",
    "    epochs = np.arange(1, len(train_losses[i])+1)\n",
    "\n",
    "    ax.plot(epochs, train_losses[i], ls=\"-\", color=hex_colors[i], lw=2, label=f\"$\\lambda$={lambdas[i]}\")\n",
    "    ax.plot(epochs, test_losses[i], ls=\"--\", color=hex_colors[i], lw=2)\n",
    "\n",
    "ax.legend()\n",
    "\n",
    "ax.set_xlabel('Epoch')\n",
    "ax.set_ylabel('Loss')\n",
    "\n",
    "ax.set_yscale('log')\n",
    "\n",
    "fig.savefig(\"./plots/losses_cr3_lambda_scan_uwu.png\", dpi=300, facecolor=\"w\")\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Image Reconstruction"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "2023-03-08 19:31:42.799363: I tensorflow/core/platform/cpu_feature_guard.cc:193] This TensorFlow binary is optimized with oneAPI Deep Neural Network Library (oneDNN) to use the following CPU instructions in performance-critical operations:  AVX2 AVX512F AVX512_VNNI FMA\n",
      "To enable them in other operations, rebuild TensorFlow with the appropriate compiler flags.\n"
     ]
    }
   ],
   "source": [
    "vae = BalleFFP(N=128, M=192, k2=3, c=3, cr=COD_RANK, format=CH_FORMAT)\n",
    "\n",
    "if CH_FORMAT == 'channels_first':\n",
    "    x = tf.zeros((1, 3, 96, 96))\n",
    "    \n",
    "elif CH_FORMAT == 'channels_last':\n",
    "    x = tf.zeros((1, 96, 96, 3))\n",
    "else:\n",
    "    raise ValueError(\"CH_FORMAT must be either 'channels_first' or 'channels_last'\")\n",
    "\n",
    "# call the model to create the weights\n",
    "_ = vae(x)\n",
    "    \n",
    "# load the weights from the .h5 file\n",
    "# vae_list.append(vae.load_weights(model_path))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [],
   "source": [
    "img, ids = select_random_images(data, 1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Loading model from: ../models/model_ffp_channels_last_epochs50_normFalse_l1e-05_cr3_20230308115252.h5\n",
      "Bitrate shape: (1,)\n"
     ]
    },
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 1400x700 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Loading model from: ../models/model_ffp_channels_last_epochs50_normFalse_l0.0001_cr3_20230308132810.h5\n",
      "Bitrate shape: (1,)\n"
     ]
    },
    {
     "data": {
      "image/png": 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fffedeuGFF1Tz5s0TfaB3796qsLBQbdy4sV75+Hk79dRT1XvvvacWLFignnnmGZWTk6OcTqeaOnVqg9tPqT3vakPte0Sld30pZf5Jfmlpqerbt68CoEaOHKk+++wzNWfOHDVmzBhlt9tVs2bN1A8//JD4/N7nraCgQBUWFib++f3+RLCpeD+cNWtWvc/o6hoP0nHUUUc1qg3i11HXrl3VlClT1OLFi9UHH3ygzj77bAVAXXzxxSoWi9Urs3ffuvXWW9Wxxx6r3n//ffXNN9+oO+64Q1mWpVJSUrSv8aiurlb9+vVTANTpp5+uZs6cqZYsWaIee+wx1bFjR3XNNdc0+if5ewcV6devnzrrrLPUjTfeqBYsWKA+++wzdfjhh9f7OeymTZtU586dld1uV2PGjFHz5s1Tn376qRo5cqQCoDp16qR9j+GcOXOUz+dTmZmZ6qmnnlKLFy9WM2fOVH/+85+VZVkKgJoxY4ZYZvz48WrJkiXqk08+UWeeeaYCoK644goVjUaNxzNw4ED14IMPqsWLF6s33ngj8ZPOBx98MKmOH330kbLb7erII49Ub775plqyZImaOXNm4vpr165d4rNFRUX1xttXXnklqU82ZgyP91dpbNq6des+g6kFg8HE9gYNGqQ+/fRTtWjRIvXSSy+p9u3b1/s5aigUqtdW8fEj/m/vn9k+9NBDiUArb775plq4cKF65ZVXEq8k0AVD2bFjh+ratasCoC655BI1d+5ctWjRInXnnXeqI488MnHPacxP8ht7Pxo3bpwaOnSomjdvnpo9e3biGh08eLDy+/1q4MCB6o033lALFy5U48aNUzabTaWlpSWNo0opdcsttygA6vjjj1fvvfeeWrx4sXrrrbfUcccdl7imdUzt0KJFi8RYOWrUKFVYWFhv3tDYsbIhHnvsMeO9U3cf7NKli3r55ZfVkiVL1MSJE5XNZlMjRozY5/lQSqlffvlFNW/ePHGMX3/9tfrqq6/U9ddfrw477DB11FFHKQDq/vvvV4WFhfXeT133J/n33HOP+tOf/qQWLFigZs6cmfjJ+N4/v44Hhoy/ozPervF/27dvT6pjTU2NstlsCoBatmxZo9qze/fu4jUZv85MwatM9/j27dsn5h2/9WszzjvvPAVAXXbZZUl58TH48ccfV4WFhWr48OGqoKBApaSkqA4dOqhrr712n6/FiWvoT/JXrFiRaMMPP/xQ+5kPPvgg8ZlHHnkkkR6ftwBQ33//vbZs3c8sXbpU+5nPPvtMAVBZWVn17j1ERL83XDAlot+tK664QgFQPp+vUeXS0tISiwB11X1g6N+/f713J8WD4NRdHJXeqffDDz8oh8OhLMtKeiF+RUWFateunfFdYft6R2K87LHHHluvjpFIJFGnvRdElNqzYHrBBRckpf/yyy/K6/Wq3NxcVVVVlZS/P+/1+uKLL4wT9PgDbEZGRlLArvgD9wUXXKCeeeaZenlTp05VANRxxx2XtM34gumKFSuS8uKLXbpFh3iQg5YtW6qysrJ6ecuWLVN2u11shwkTJigAqm/fvknv3CosLFQ2m015PJ5GvbctvqDTqlUr4+dMC6YXXXSRAqBuu+22pLyJEycmFiP3rvO+zptSDX+HqVIq8RDrdDq1i/mSZ555RqWmpqri4uKkvAEDBigA6q233tKWjbdLenp60sLi5ZdfLi68xN/NdvTRRyct/n700UeJh/2mvMM0fi3Z7fakd8PFA6IotSdQTHxxaNKkSUnbGT16tAKgzjzzzHrpmzdvVpmZmcqyLPXVV18llbv55psVgHp/HImXAaC+/PLLep8Ph8PqhBNOUADUfffdZzyeJ598sl7e559/rgCo/Pz8pAfeHj16KADa62HgwIHafteQd5g2Zgxv6Niku65uvfVWBUANGDAgacF+06ZNKiMjI+mPAw0ZR2fMmJFYMK6urq6Xt23bNuXz+bTn9pJLLkks3u7tmWeeSfTZprzDtKH3o759+9Y7zzU1NYkI4EOHDk0aj+Nj8ZgxY5K2ecstt6jWrVsrv99fLz0YDCaCNy5atCip3L7aIV5XXTs0daw0ufLKKxWw54+UJvG+5vF4koLjDRgwoF7bm85HfMy4/vrrk/Lii9BSn6577QwdOrRent/vT8ybVq5cmVS2se/IbdGihQIgvndTJxQKKYfDoQCozz//XPyc6V2s+7rHO51O4zV62WWXKZ/PpyZMmNDgeu9LeXm58nq9Yp9u3bq1AqAGDhyoXC6XGjVqlPryyy/VN998o0aPHq3sdrvKyMhQX3/99T731dAF02AwmKiTFK3+0UcfTbTz7bffnkivu5Cq+2OIUnuCR+5rQXb16tWJz2zYsGGfx0ZEdKjwJ/lE9Lu1a9cuAEBaWlqjyvl8vnrldW688UbY7fbE/2/RogXWr1+P448/fp/bf/zxxxGJRHD66aejT58+Sfv+61//2qj6Sq6++up6dbTb7Ymfqul+djty5Ej885//TEo/7LDDcMIJJ2DXrl2YM2fOAalbY5133nlJP/2K/1T1448/xp/+9Kd6efGfjC9duhShUKheXufOnfHkk0/iyCOPTNrPlVdeCQB466236qUrpfDoo48CAEaNGoWMjIx6+T179sTZZ5+trXswGMS9994LALjzzjvrnRNgz/vJBgwYgEAggGeffVa7DZ21a9cC+P8/fWusZcuWYdq0aXA4HBg7dmxS/siRI+Hz+fDzzz9j5syZTdpHQ+Xl5QHY827UTZs2NbjcscceiwkTJqBFixZJeVdccQWA5HO5t3PPPRctW7aslxbvP3tfJ36/H5MmTQKw5/3Ie7/DddCgQTj88MMbXH+JZVm45ZZb6qVdcMEFiVdQTJ8+Hd9++y2aN2+OkSNHJpWPl509e3a9n5I++uijKCsrw6mnnoqTTjopqdwNN9yQlPbII48kyvTr169ensPhSLx77+GHH0ZZWZn2eOx2O/785z/XSzv55JNht9uxY8eOxHHFrVmzBoD+J6gjR47E6aefrt1PY+zPGG6ybdu2xPsX77jjjqSf/rZu3RoXXnhhk7Ydv05Hjx4Nr9dbL69Zs2a47LLLoJSq91Py9evXJ36mfvvttydt8y9/+UvSeHYwXH311bDZ/v9jg8fjwXHHHQcA2L59e9J4HL8G4z/frWvAgAEYP358Uv9wuVy49NJLASDxupK4hrRDVlaWtu4Ha6xs7Bh+zjnn4IgjjqiXNnXqVDz22GP7LDtv3jx8++23AIAxY8Yk5d922231zo/JX/7yl3r/PzU1NfEuS9OrTBoqfj+It09DbNy4EZFIBEDT7okNuccPGDBALL9r1y5MnToVlZWVjbqP78v48eNRU1ODP/3pT4nrpa74mPvJJ5/gb3/7GyZNmoR+/fqhb9++eOSRR3D//fejvLwcF110ESorKw9InVwuV+IVAs8//zyi0Wi9/Gg0ihdeeCHx/2tqahL/HX8FBwC43W7t9uum+/1+7WfifQRoXD8hIvqtccGUiH63VO37r6R3Ve1POd1Ddbt27eDxePa5/U8//RSA/N7J+Mvy91f8PVB1xd9XVfcdVHEjR44U3ynVqlUrAP9/IeO3pqtX/KGoc+fOSElJqZcXn0xHIhGUlJTUy+vcuTNuvPFG7X6k4/z5558TizqNPW8LFizAjh07YFkWTjjhBO1nOnfuDGDP+wsbKv6gtPfCSUO9//77APYs2OoWTBwORyKIRGPq1RR1j0FadNM59thjxXf1NbTPNuY6+eqrrxIPcAfz+u3UqROys7PrpXk8nsT7NOPn7vjjj09agAf2LJ7Fz2ndcxcvp3svJgC0adMGs2fPrtdP4+8xlMrE0/1+P2bPni0ez95/uHI6nYlreO927tixI4A9f8DY+2H4/PPPx8svv6zdT2Pszxhu8vHHHyMUCsHlconX+z//+c/EwntDrVu3Dj/88AMA4MQTT9R+RjeOfPrpp1BKweVyaY/Z6XSKgVsOJNMYrsuLj+Hbtm1LyhswYID2HdGAfN3vTzscrLGysWO4rt65ubkNWiCML+R26NAh0UZ15efn7zMwZtzRRx+dlBb/g6ZubtFY8fZozL2g7mebck/cn3s8sOc8DB8+HGlpaUkLyk21evVqPPDAA4k/8urE3/Fps9lw2223JeXfeOONSEtLw7Zt2xLvkj0QHn74YXTu3Bnr1q3DxRdfjF9//RWxWAxr167F8OHD4ff7E18+qPuHjfj8en81dc5ARPRba3hIPSKi31j8gauxf1WPL4iYHkJycnKaVKeysrJEcIg2bdpoP5Ofn9+kbe9N922Z+GKALrBRKBTCc889h3feeQc//fQTKioqEkFz4v8r/bX/YNMdS3yhSJdXN+Kr7liXL1+Op556Cl9//TW2bt2a9Jm9j3P16tWJ/27seYtHtlVKiX0q3r6NCRoU/9ZGUyPVx+u1YsUKMUJu/JsjTQ1m1FAulyvx31KQB8n8+fMxceJEfPvtt9ixYwfC4TCA//9gtq8+25jrJN4PbDabdtEBODDX777Gl/i5mz59eoPPXUVFReK/27ZtK277jDPOSPx33TJ7Bz+KS0tLQ05ODkpKSrBq1SpcfPHFSZ+RvrkntfNjjz2GCy+8ELNnz0anTp1w0kknYciQIRg6dKix7o3R1DF8X+LnpqCgQDw37dq1E9tzX9sF5MjU8T6/a9cuBAIBeDyeRJ8tKCjQLq4DB+6eY9LUMVwKwjd9+nS89NJL+P7771FSUpL4dqF03e9POxyssbKxY/j+9Nn48Uv3L2DP8f/666/73Nbef8wBzHOLxorfDxpzL6j7Lcam3BP35x4f9/rrrzd6v5Ldu3dj8ODBSE9Px8yZM5Genq79nMfjQVVVFQ477DBt/TweD3r37o158+Zh7ty5uP766w9I/bKzs7Fw4ULccccdeOONN9CpUycAe74dOnjwYCxatAjHHHMMKisr613fdf9wJvWVuunSL8T2Z85ARPRb4oIpEf1uxX+6VllZiZKSkgY9bOzatSvxoNW9e3fxc9ID177UfYiTvgXR1AWwvTWmjjU1Nejfvz++/fZb9OzZE8888ww6d+6c+GnUnXfeienTpx+wbwc0lumngg39GWHcO++8gz/84Q+w2Wy48cYbMWDAADRr1gzAngjCZ511VlKZ/Tlv8cjBbrcb3333nbFujTln8QeGvX8O11Dxep144on7/Amh9LB2oMQXOwD5Z3o6TzzxBG655Rb4fD6MGTMGJ510UuI6X7JkCf70pz/ts882ps3j/SAetV7nQFy/+6pT/NxdfPHFuOuuu4yfjbdH3QjWDf0GVkPLxPPKy8u1+Y0dL8855xwsW7YMjz/+ON5880189dVX+OqrrzB69Gicd955mDhxYtJrFBqrqWP4vsTbrKnf/N7XdgFgzpw5+7yfxfthvM+a6nOg7jkmB3IMv+GGGzB+/Hg0a9YMY8eOxTHHHJP45uf06dNx5513Jl33+9MOB2usbOwYvj999kD2g8aer8aK3w8acy+ou4DWlHvibzk325eamhoMGTIEO3fuxJw5c4zf/M3KykJVVVW9n6jvLf7KmqKiogNaz+zsbDz77LOYMGECioqKEIlEUFBQAK/Xi1gslrhu6r6mpu4fGktKSrSL03VfhyWN802dMxAR/da4YEpEv1tnnHFG4v16S5cuNb5/Ku77779P/HdDPt9Ydf9aXvcbEXXFvyH3W5owYQK+/fZb5ObmYu7cuUnf+MnMzPzN63QwBINBXHvttYhEIrjvvvtw55131suXvs2wP+ct/rO0YDCIrl27it9Qaqy6292f8oD5jwO/hYZ8o2RvxcXFiXcRTpo0CZdffnm9fNM7iJsqXrdgMAillHbR9Le4fuPnzuVyNfjc1V3IkfpwU8vE8w7kuzC7du2KF198EePHj8dHH32EKVOm4OOPP8b06dPx/fffY9WqVfX68G9NWpSJt1lD27ih6h5rq1atEq8t2Jd4nzXV51Dcc5pqyZIliXfETps2LeldvNIfpfanHQ7WWLm/Y3hj/Cf1g3h7NOb983XPUVPa8/cyNwsGgzj//POxYsUKfP7559rXH9R1+OGHo6ioyLhIfLD/0G2325O++V9UVIRQKATLsuq99qZr166w2WyIxWLYvHmz9vji39K22Wzo2rWrdp9NmTMQER0KfIcpEf1u9e7dO/EOuffee69BZd59910Ae95hddRRRx3wOmVmZibe9SUFtzkQ7wBrrPh7144//njx57P/DQoLC7F7924Ae77F1lB1J+2NPW91H7BNP3d87bXXEu+3bYj4NzPix9NY8Xr98ssv4md27tyJl156CStWrGjSPhoqvrhpWVaDf3L9zTffJB5gG3Mu90e8H8RiMfHbOr/F9duQc7d+/Xq89NJLWLduHYA9C3nxPrNx40axXFVVFQKBQFKZDRs2aD/v9/sT7wk+GAvvXq8Xl1xyCT788EMsXLgQqamp2Lx5c4PH9KaKf2Nt76BxcdJ1F2+D4uLiet+CqiscDsPv9ydexdEQddvWdN7fffddTJs2LfH/433WVJ9Dcc9pqvi9yufzaQOXSfanHQ7WWLm/Y3hjxI/fFFTv99IP4veDxry2ou43FZvSnvtzjz9QwuEwLrroInzzzTf45JNP6gUFDQQC2LBhQ1Lfjb/PeMuWLeJ24+8BPlCvM2mIr7/+GgBw0kkn1QvKmJqamngX7PLly7Vl419cOPHEE5PeTx9X9w+ijX29CRHRb4kLpkT0u/b444/D6XTitddeEx/449avX4/XXnsNLperQVFnmyq+uCMFh9BFBT7Y4t9AkL6JcLDfYflbqXt8umOVjrNLly6Jn8U19rydeOKJiZ/8z5o1S/uZJUuW4KqrrmrUuY//zG3btm1N+gZJPFL39u3bxYf8V199Fddcc02THkDjPx+tW7dPPvmk3re447Zu3QpgTwRx6QFpb3W3q1t4Ohh9tl+/folvMh3K6zd+7pYuXSp+k/axxx7DyJEj66VdcMEFAPZEzNZZvXo10tLS8K9//SupzBdffKEtE09PS0ur9/7T/dG8eXN8/PHHSenHHnts4pv/ewcDin9zu26/mDdvHr766qsm1SF+ze7atSvp21t+v19cPDv33HPhdrsRCoXwzTffaD9zxRVXoFmzZvUiRuvqv2PHDkybNg0lJSXo0KFDIjiSNI5s374dw4YNw0cffZRIO/vss2FZFkKhkDaCeTgcxtKlS7Xb+z2qe69qzBi+P+1wsMbK+BgeH/8OpoEDBwLYEzxM10Y7duxI/HHlQNP17VWrVmn/6BGLxRLveZe+XaiTlpaW+Ll3U9pzf+7xB0I0GsUf/vAHzJkzBx999FFSYLdFixahffv2SX+oGzZsGCzLwubNmxNBq+oKBAKJb12fffbZB6y+s2bNQq9evcQYAVOmTAEA3HzzzUl5V1xxBQBgxowZ2rLx9L1/NVJX/By7XK4GBysjIjoUuGBKRL9rxx9/PCZMmIBgMIjBgwcnJuJ72759O84//3yEQiE8++yz9f6yf6DdcsstcDqdmDt3LpYsWVIvz+/37/MdaQdD/Ju4X3/9ddJCxJo1a7BgwYLfvE4HQ48ePRILXu+8805S/iuvvKItZ1kWxowZAwB47rnnkt7VuGLFCnz22Wfasm63G3fffTeAPQv4ez9Qx2Ix3H777Y2Ortu3b1+4XC5UV1c36d1kPXv2xCWXXAIA2nf+bdu2DY8//jiOOeYY9O/fv9HbjwegiEewjUQiuPjiixNR1+v68ccfAaBR+znuuOMS79Kr+426uMmTJzeyxvuWmpqaCJrxxBNPJP1Ec8aMGfWC8xwsgwcPxvHHH49IJJLoW3WtWrUKr776Ki644IJ6D5OjR49GVlYW5s2bp72mH3roITidTlx11VVJZebPn5+0+BiNRvHQQw8BAG6//fYD9uqO7du3J77tX1c8CjOQHPho7/4GACNHjsSLL77YpDq0b98eeXl5CIfD+Pbbb+vlvfjii+K3Q5s1a4YbbrgBAPCvf/0r6br66aef8OGHH2L48OH1fkasq//nn3+Oiy++ODHePPDAAwBQ75vDdcXHqBtvvDGR1q5dO1x66aUA9kS23tvzzz+P0tJS7bH8HsXvVX6/P+kb+aFQCFOnTtWWa0g7SO/gPVhjZTwae92AQwfLySefnGg73fE/8sgjB23fur799NNP1+uncevWrUMwGITH4zFGpdfZn/ZsyD1+X78AueKKK5Ceno5JkyY1at+xWAwjRozARx99hA8++KBRfahr164YMWIEAOD+++9Pyn/qqafg9/tx2GGHGRcgG6u0tBTLli3DG2+8kZT33nvvYebMmRg8eDCGDBmSlP+nP/0JnTt3xpIlS5L++PPxxx9j2bJl6Ny5M/74xz+K+4/PGfr27ct3mBLR75siIvoP8Pbbb6usrCyVnZ2txo4dq2bPnq2+//57NXv2bDV27FiVnZ2tsrKy1LRp07TlCwsL1axZsxQABUAVFhaqwsJCVVpamvTZ1atXq8LCQlVQUKAAqFdeeUUVFhYqv9+f+MykSZMUAJWXl6defPFFtXTpUvX++++r3r17qzvuuCOxn7q2b9+uCgsL1ahRoxQAdf7556vCwkJVVFRUb7/xsrNmzVKrV69WSinl9/u1Zbdv366UUqqsrEx16tRJAVBdu3ZVU6dOVd9++616+eWXVcuWLZXP51MA1KhRoxLHXVpaqgoLC9X999+vAKjevXurwsJCtW7dun2ej3h9XnnlFQVAFRQUqMLCwkR9i4qKVGFhoerdu7cCoO6//35VWFioQqFQouze+40fy7p165LaobCwMLHviRMnKgDKbrerG264Qc2bN099/vnn6qqrrkocZ/wcx+ujlFKxWExdeumlCoDq1auX+uCDD9TSpUvVCy+8oNq3b69uuukmBUCdcsop2mP++9//nmjfKVOmqO+++069++67ql+/fsrhcKi33357n+22t4EDByoA2rLxdti7Dev22fLycnXSSScpAOqcc85RH3/8sVq8eLF66aWXVNu2bVWzZs3UTz/9tM/zVrf94/74xz8qAGrEiBHq22+/VbfeequyLEt98803SXU95ZRTFAD1wQcfNOr4R48erQAoj8ej7rnnHvX111+rTz75RJ177rmJcxmvY7xfmvqWUkp7fHX7dE1NTaK+p59+uvr000/VkiVL1OOPP67y8/PVoEGDtNenidSn69Zrb0VFRerwww9XANTll1+uPv/8c7Vw4UL11FNPqdzcXNW5c2e1bdu2pHJffPGFSk9PV1lZWWr8+PFqyZIlaubMmWr48OEKgHrppZf2Wea7775TM2fOVGeeeWZi/9FodJ/HE+8j8XOw9xgZP9b4NXjVVVepTz75RH333XdqxowZavDgwQqAGjZsWFIdx40bpwCos88+Wy1atEg99thjCoB64403Eue1oWN43AMPPKAAqPbt26t33nlHLVmyRD300EPq3HPPVf369avXf8rKyhLlQqGQGjp0qAKgzjvvPDVr1iy1aNEiNWnSJFVQUKCOOOIIVV5eXm9fFRUVKj09XdntdjV16lT15Zdfqp49e6ojjjiiXts+9thjyrIsVVBQoF544QW1ZMkSNWPGDHX++ecrAOqJJ55IOo5du3apI444QgFQl1xyifriiy/UokWL1F133aUKCgrUqaeeWm983/ta1tmf+1G8bLzO8f3G75H7ugYvvvhiBUBlZmaqJ554Qi1cuFB98MEHqm/fvonrPt7n6l5/pnbo0aNH4pzdfffdScfb2LGyIQKBgMrOzlYAtG0ujVW6e+y+zodSSq1du1a1aNFCAVDXXXedWrBggfr666/V9ddfr0455ZTE8U2ePLnetnXXTrwO8XnA3uey7nU1f/58BUC1bdtWzZ07V7333nsqMzNT/eUvf0k6jsmTJysAasiQIY1qS6X2zPMAqIEDByblhUIhcQyIM93jW7RokegfurnOzp07E9vt3r17o+p9/fXXJ+Ykqamp2n8ej0cBUOvXr08q7/f71QknnKAAqD/+8Y/qyy+/VAsXLlSjR49WdrtdtW7dWq1atUq77/j5qzte172v150D1fXGG28oAColJUU98MADauHCheqLL75QN910k3I4HOqss85SVVVV4jGvWrVK5eXlqYyMDPXss8+qxYsXq0mTJqn09HSVl5cn1jduxIgRCoB66qmnjJ8jIjrUuGBKRP8xSktL1cMPP6z69eun8vLylNPpVLm5ueqkk05S//rXv4wPzvGJ8N7/9n6wUEqptm3baj/7xRdf1Pvcp59+qk4++WSVmpqqfD6fOuGEE9R7772n1q5dqwAoh8NR7/N33323drsjRowQ99u2bVul1J4FD13Zug+Gu3btUn/9619VmzZtlMPhUBkZGap///7qnXfeSUxO6x53/MFm73/SgmFdUn3i9d17f/F/69ev3+exxBez9v5X1wcffKD69eunUlNTlcvlUh06dFB/+9vf1MKFC7X1iYtGo+qZZ55R3bt3V263W+Xm5qrzzz9frVixQr388ssKgDrjjDPE4/7444/VOeeco3JycpTD4VDNmzdXw4YNU0uXLt1nm+l88sknCoC69NJLk/Kkdti7z4ZCITVhwgR13HHHqbS0NOVyuVTHjh3V3//+96QFN6ntdYsMJSUlavjw4SorK0t5PB7VrVs39dprryXVs7i4WDkcDtW+fXsViUQa3QYvv/yyOuaYY5TX61Uej0cdfvjhauzYsWr69OnafmnqW0rpr/W9+3QgEFD33nuvOuyww5TL5VK5ublqyJAhavny5UnXafz6NDG1q+4BOc7v96sHHnhAHXXUUSolJUW53W51xBFHqDvvvFNVVFSI5TZu3Kiuu+461b59e+VyuVR6ero6/fTT1ccff2wsM2rUqESZrKwsddppp6m33nqrwccT7yP7OgerVq1SY8aMUX379lWtWrVSbrdbtW7dWp1++ulq2rRpKhaLJe2zpqZGjRo1SuXn5yuXy6UOO+ww9cgjjyTyGzOGx8ViMfXwww+rjh07KqfTqVq3bq3GjBlTb9E8/u/f//53UtkpU6aoU089VWVkZCin06k6dOigbr75ZrV7927t/ubMmaN69+6t3G63ys7OVuecc452Ee6bb75RQ4cOVc2aNVMOh0Pl5uaqQYMGqblz54rHUlZWpm6++WbVunVr5XQ6VYsWLdRll12m1q9fn3Q+dAuGe9uf+5FUNn6P3Nc1GA6H1aOPPqq6deumXC6X8nq9qmfPnurhhx9Wzz//vPH6q9sOLpdLtWrVSl177bWqpKREXXHFFQrYszCp05ixsqFuu+02BUA999xzSXnSdaK7x+7rfMQVFxerq6++WjVr1ky53W7VoUMHNWbMGFVdXZ34I8CUKVPqlTHVQZoH7H1djR8/PnEdFRQUqJEjR9b7I0PcueeeqwAY+7IkFAqpli1bKq/XmzSfW79+vTgG1LX3PT4rK0udeeaZ6osvvkg61r3Pw/Dhw1VaWpqaMGFCo+p91FFHiXVr6P0gFAqpJ554QvXq1UulpaUpr9erunfvru68805VUlIi7ls6f3tfs3vbuHGjGjt2rOrbt69q3ry5cjqdKj8/Xw0YMEBNnTq1QcddXFysRo0apdq0aaNcLpdq3bq1GjVqlCouLjaWCwQCKicnR/l8Pm0fIiL6PbGUOsih94iI/scsW7YMvXr1QosWLVBcXHyoq0MN9OSTT+Lmm2/G8OHD8frrr/9m+z3zzDPx5ZdfYtWqVTjssMN+s/0eKDfffDOefPJJvPfee4n3ZRIR/dbOP/98fPjhh3j++eeT3v97sJSWlqJLly7Izs5GYWEhnE7nb7JfnaOOOgo//PADZs2alXhX8G9p2bJl6N27NwYNGoTp06c3aRtTpkzBFVdcgXvvvRd33XXXAa4h/R6MHz8eN9xwA5544gncdNNNh7o6RERGfIcpEVET3HfffWJwimXLlgHY8/5V+v0oLi7GuHHjxABLh+q8TZ48Gbm5ufjjH/8oRvT+vfr888/xzDPP4Prrr+diKREdVAsWLMBrr70m5sejdv+WY3hWVhamTJmCtWvX4o477jio+5oxY4a4EFldXY01a9bAbrejd+/eB7UeOpWVlRgxYgTatWvX5PcOA3sCBV155ZV48MEH/6OCmVHDFBYW4s4778TgwYMT74omIvo944IpEVETPPzww9rAAOFwGBMnTgQAXHfddb91tciguLgY99xzjza406ZNm/D+++8jPT39gAZWaIhWrVphzpw52Lp1qzbAwu/Vl19+ifPPPx/XX389nn766UNdHSL6L7dw4UL8/e9/x86dO5Py3nvvPWzatAknnngijjzyyN+0XgMGDMA777yDSZMmHdTgS59++iluvvlm1NTUJOU999xzCAQCuPTSS5GdnX3Q6qATCoVwyimnwLIszJkzJxEkqqleeuklDBs2DAMGDMDPP/98gGpJh9rPP/+M/v37Y+DAgXjzzTcTQR+JiH7PHIe6AkRE/6keeeQRBAIBnHfeecjKysK6devw5JNP4vvvv8fYsWNxxhlnHOoqksYf/vAHjB07FscffzzcbjeWLl2Kf/3rX4hEInj77bd/84dNYE+k3O+//x5PPvnkb77vpqqsrMQHH3yAM88881BXhYj+R1RUVKB///4YM2YMunbtilAohNmzZ+ORRx5B69at8X//93+HpF5DhgzBihUrtH+QO5DWrVuHM844AzfeeCM6dOiAyspKTJ8+HePHj0ePHj0wfvz4g7p/nVAohAsvvBC33HILvF7vfm/P6XRi8uTJeOedd1BWVrb/FaTfhbKyMkyYMAGXXnrpoa4KEVGD8R2mRERN8NVXX2HatGn48ssvUVxcjN27dyMzMxPHHnss/vrXv2LgwIGHuoq0l1AohI8++gjvvvsuli1bhm3btqGqqgotWrTAaaedhltvvRXdunU71NUkIiKNkpISvPPOO5g+fTrWrFmDbdu2QSmF9u3bY/DgwbjllluQm5t7qKt50BQVFeHtt9/GRx99hPXr12P79u2w2+3o3LkzLr74Yvz9739Hamrqoa4mERHRfw0umBIRERERERERERHV4stDiIiIiIiIiIiIiGpxwZSIiIiIiIiIiIioFhdMiYiIiIiIiIiIiGpxwZSIiIiIiIiIiIioFhdMiYiIiIiIiIiIiGpxwZSIiIiIiIiIiIioFhdMiYiIiIiIiIiIiGpxwZSIAABlZWV49tlncc4556B58+ZwuVzIyspCv3798MwzzyAYDIplt23bhsceewz9+/dHbm4unE4n8vLycOaZZ+L//u//EIvFGlSHpUuXonv37rAsC/PmzWtU/WfPno3WrVvDsixs2LChQWVWrFiBK6+8Em3btoXb7YbP58PRRx+NcePGobKyslH7HzZsGCzLQrt27RpVDgBOPfVUWJaV+Pfqq682qnwgEEDfvn3RpUsX7Nixo9H7JyIiIqL6wuEwxo8fj759+yIjIwMulwsFBQW48MIL9zlP9fv9uO+++9CrVy/4fD643W60bdsWV1xxBZYtW7bPfc+ePRtnnXUWcnJykJaWht69e+PZZ5+FUkosc9VVV9WbT+r+TZkyRVt24cKFuP7669GjRw+kpaXB4/GgQ4cO+OMf/4jly5fvs777qss999zTqPJKKQwZMgQtW7bEjz/+2Oj9ExEdCFwwJSIsXrwY7dq1w3XXXQelFCZNmoRvvvkGkydPRiwWw9///nccd9xx2LVrV1LZDz74AO3bt8fo0aPRokULvPLKK1i0aBHGjx+P4uJijBgxAmeddRZqamrE/UciEdxzzz04/vjjsWrVqkbVvaqqCtdddx3OOussFBUVNbjcm2++iT59+uDNN9/EiBEjMGfOHLzxxhvIy8vDPffcg6OPPhrFxcUN2tbMmTPx9ttvN6redU2ePBmFhYXo3bt3k8qvXLkSixYtwpo1a/DVV18l5ccnrY2drBIRERH9L/L7/TjllFNwww03IBQK4ZVXXsH8+fNx6623Yvbs2ejfvz8eeughbdlt27ahV69e+Oc//4nc3Fy8/vrrmDNnDq666iq89dZbOPbYY8WFSwB47LHHcNZZZ6GiogJTpkzBrFmz0K1bN1x33XUYMmQIotGoWNbhcCA1NVX853Q6k8oMHz4cJ5xwAqZOnYrLL78cM2bMwLx583DVVVcl5svPPvtso9rvgQceQGFhIc4///xGlYsrKSnB9OnTUVxcjJkzZybl33PPPbAsC1dddVWTtk9E1CCKiP7nvf/++wqAuuCCC5LyQqGQ6tatmwKgBg0alJT/5JNPKgDq5ptvTsorLS1V+fn5CoC6/vrrtftes2aN6tWrl0pPT1cvvfSSAqAAqC+++GKf9f72229Vx44dVfPmzdX48eMTZdevX28st3PnTpWWlqYAqPHjx9fLi8Vi6phjjlEA1NChQ/dZh6qqKtWuXbvE9tq2bbvPMpJTTjlFAVCTJ09uVLlIJKKuvPJKNWjQIFVZWZmUP2LECAVA3X333U2uGxEREdH/ijFjxigAqlWrVqq6urpe3vTp0xUAZbPZ1IoVK5LKDhs2TAFQvXv3VrFYrF7e008/rQColJQUtW3btqSyc+fOVZZlqfbt2yu/318v78ILL1QA1Lhx47R1HjFihBoxYkQjj1Spo446SjkcDrV06dKkvKlTpyoAyrIstXjx4kZve3/moKNHj1b9+/dXRUVFSXl33323AtCk4yUiaih+w5SIEsaOHZuU5nQ6MWbMGADAjBkzsHnzZm3Z22+/PSktMzMT119/PQDglVdeQSAQSPrMxx9/jKysLBQWFuLqq69uVH3feOMN9O7dGytXrsR5553X4HIff/wx/H4/LMvCn//853p5lmXhmmuuAQB89NFHxlcRAMDdd9+NnTt34rbbbmtU3Q8ku92O1157DR999BHS0tIOWT2IiIiI/hu89dZbAIArrrgCXq+3Xt7gwYPRvHlzxGIxvPvuu/XyQqEQPvjgAwDANddcA8uy6uXH06qrq/HJJ58k7Xfs2LFQSuGWW25Bampqvbx//vOfAIBHH30Uu3fv3q/j29tZZ52FXr16JaX/4Q9/QMeOHaGUwnPPPXdA97kvjzzyCObOnYuWLVv+pvslIorjgikRoVOnTrj11lvRs2dPbX737t0T/733T+aPOeYYjBs3Dnl5ecay1dXV2neLDhs2DLNnz0abNm0aXe/Ro0fjzTffRE5OTqPKxX9qn5+fnzQJBpCoSygUQllZmbid5cuX46mnnsK9996L1q1bN6oORERERPT7FJ8rSvPTePre744vKSlJ/LFdV9br9SbmzHuXXbt2LRYtWgQAGDRoUFLZo446Cq1bt4bf708syh4II0aMwHXXXSfmd+vWDUDyMwAR0X87LpgSEbp164ZHH30UDodDm1/3r+N7/7W7X79+ib94N7YsALRo0SLpr+8NVVBQ0KRy8cXNkpIS7Xugtm/fDgBISUlBfn6+dhuxWAwjR45E9+7dccMNNzSpHiYrV67E0KFDkZeXB6/Xi6OOOgrPPfdc0sv+TS/Vf/XVV2FZFl577TUAwLhx48TPBgIBTJgwAcceeyzy8vLgdrvRqVMnXH311Zg1axYikcgBP0YiIiKi36P4XDE+J9xbPL19+/b10vPz8+F2u8WykUgk8e3QvcvOnj0bAJCVlYW2bdtq9xv/Fmj8swfCTTfdhIEDB4r58Xm6bh7fGJs3b8aIESPQokULeDwedOnSBf/6178QCoXqfS7+ftL4v7rvKZ03bx4sy8K4ceMAAK+99pr42Wg0in//+9/o168fWrRoAZfLhbZt22L48OF47733tL98IyKqiwumRLRP69atA7BnAfGoo45qUtlWrVqhVatWB7xuTXH22WcjMzMTkUgEH374YVL++++/DwD4y1/+Ii7mTpgwAUuXLsULL7wAu91+QOv3ww8/YMiQITjnnHPw6aefYurUqYjFYhg1ahT++Mc/1vus6aX6Q4YMqZc3atQoFBYWJv7Fv00QiURwxhln4O9//zv69++PadOmYf78+bjxxhvxySef4Oyzz8bUqVMP6DESERER/V4NHz4cwJ7gpnv/sXrp0qXYtGkT0tLScNlll9XLs9vtuPjiiwEA7733XtJ2P/roI0QiEbRq1Qrnnntuvbz4NzhNv1qK50nf9ty5cyfGjBmDHj16ICMjAzk5OTjxxBPx1FNPGQOwmsTn8n379m1SeWDPN3ZPO+009OzZEx999BHee+89NGvWDHfccQcGDRqEcDic+Ox1112HwsJCjBo1Kmk7ffr0qZd3/vnn15vbPvDAA4nPXnbZZbjyyivRpUsXTJkyBQsWLMC4cePw3XffYejQoXj44YebfDxE9L9B/3UyIqI64u9nGjFiBNLT05tU9m9/+1uTv0l6oMUjll522WUYNWoULMvCGWecgfLycowfPx4ffvghRowYUW/SVVdRURHuvPNOXHfddejTp88Br9/EiRPx3XffoUePHgD2vPbg5JNPxuGHH47XXnsNZ555ZmKC3rJlS7Rs2RKZmZlJ28nMzEz8A/Z866Hu6xXiPvzwQyxYsACXX355vcnj8ccfjz59+uC4445LelggIiIi+m/1j3/8A6tWrcL777+PESNGYNy4cWjevDm+/fZbXHPNNWjWrBlef/117fs1n3jiCWzYsAEffvghbrvtNtxwww3IyMjAnDlzMGrUKHTq1AnvvPNO0jc2i4qKAMD4qqnc3FwAwJYtW7T5n3zyCWpqanDPPfegffv2KC4uxsSJE3HTTTdh8uTJ+PTTT9GiRYsGt8Mvv/yCwsJCOJ1OXHvttQ0ut7eXX34ZM2bMwDnnnJNIO+2003D00Udj9uzZeOSRR3DHHXcA2DNfjf/bW2pqKrp3757Iy8zM1M5tv//+e7z11ls46aST8NJLLyXS+/Tpg9NOOw1dunTh3JaI9onfMCUio19//RXvvvsu8vPzce+99zaq7FdffYVvvvkGRxxxxEH52fr+OOecc7Bq1SqcccYZuOCCC+Dz+dCqVSs8++yzeOqppzBp0iTt+00B4Prrr4fP5xMXVPfXWWedlVgsjcvNzU0ExXrooYcO6P7WrFkDQP9Tq2OPPRaXXHIJ39FKRERE/zNSUlLw3nvv4c0338TcuXPRoUMHpKSkoH///mjTpg0+/fRT9O/fX1s2Ly8P8+bNw8SJE/HSSy+hVatW8Pl8GDJkCE4++WR8+umn2l9sVVVVAUDiJ/068Ty/35+U17VrV9x0002YM2cOhg4dil69emHQoEH45JNPcMEFF+CHH37AJZdc0qh2iP8h/a677tqvX4p169at3mIpAHg8nsTzwZNPPrnPQKuNYZrbtmnTBtdccw06d+58wPZHRP+duGBKRKJYLIZrr70W4XAYr7zySuKv2g0RCARw7bXXIiUlBf/+97+Nk79D4dNPP0WvXr3w0Ucf4ZFHHsGXX36JmTNnYsSIEbjpppvQrVs3fPvtt0nlPvjgA0yfPh1PP/10o79t21DST55OPvlkAHvebyp9s6ApOnbsCGDPO08nT56c9L7St956C6effvoB2x8RERHR71llZSWuuOIKDB8+HD169MC0adOwaNEiTJ48GZs2bULPnj1xww03JL1/E9jz7tJzzz0Xf/3rXzFw4EBMnz4dCxYswMSJE/Hll1+iS5cuePDBB5O+4bi/33i8/fbb8cQTTyT9osuyrMQf27/++mt8/vnnDdre/Pnz8corr+Ckk07CP/7xj/2q277mtiUlJfjuu+/2ax91xee2n332GR599NGk1xGMHz8ef/jDHw7Y/ojovxMXTIlIdNttt2HOnDkYP3580nuWTJRSuPLKK7F69Wq88cYbiRfU/17MmTMHAwcOxM6dOzF//nyMHj0a/fr1w9lnn41nnnkm8VOqAQMGYNOmTYlylZWV+Nvf/oaBAwfioosuOmj1i0dP3VvdaKurV68+YPu78MILcfrppyMYDOJPf/oTWrZsiZEjR+KTTz5hsCciIiL6nzNo0CBMmTIFQ4cOxcyZMzF06FAcd9xxuOqqq/D999+jVatWGD9+PG677bZ65QKBAE4++WTMmjULt9xyC6ZMmYLBgwfjhBNOwHXXXYfvvvsOHo8HY8eOxdNPP12vbFpaGgAYv2kZz4t/tqE6d+6c+LXQrFmz9vn59evX4+KLL0bnzp0xffp0MTBsQ/3Wc9s+ffpgxIgRUErhtttuQ/PmzXH55ZfjnXfeYbAnImowLpgSkdaECRPw+OOP4+6778Zf//rXRpUdPXo0pk2bhhdffBGDBw8+SDVsuvvuuw9KKQwaNAg9e/ZMyr/++uuRk5ODiooKPPvss4n0O+64A7t378bEiRMPav2kSWndVwRUVlYesP3Z7XbMmjULL774Io4++mjs2LEDL774Is4991y0a9eu3rufiIiIiP6bzZs3D19++SUAJN6rWZfP58PNN98MAHj22WfrzcnefPNNrFmzBpZlacu2atUKf/rTnwAAjzzySFIesOfblpJdu3YBgPbdqfsSL7Nx40bj53bu3ImBAwciJSUFs2bNQnZ2dqP3tbffem4L7Pnl1Ntvv42TTz4ZlZWVmDp1Ki655BK0atUKDz74IGKx2AHdHxH99+GCKRElefnll/H3v/8dt99+O+65555Glf3nP/+Jxx9/HJMmTUqK6P57sWTJEgB73qek43A4Eu81Wr58eSL9ww8/RHV1NQ477DA4HI56/+LvF924cWO99H1NSnWkb3XW/TmRz+dr9HZN7HY7/vznP+P777/HqlWrcOedd6JVq1bYsmULrrnmmqRvQRARERH9N4rPE202Gw4//HDtZ+JzyFAohB9//DGpbIsWLZCVlWUsu3XrVmzfvj0pffPmzWLd4nnSHNYk/pN/UxDW0tJSnHnmmaisrMTcuXPRtm3bRu9H51DMbQHg4osvxvz587Fu3To89NBD6Ny5M0pKSjB27FjccsstB3x/RPTfhQumRFTP1KlTMXLkSNxwww148MEH6+UVFRWhrKxMLPvggw/ivvvuw1NPPZUUSXPDhg3aF9QfCo15R1Tdv4h/9tlnKCwsxPLly5P+xQNiFRQU1EsvKChodP127typTa/7eoAuXbo0ersNdcQRR+C+++7D2rVrcdlllwEAnnrqqYO2PyIiIqLfi8a+S7TuXHF/yp555pkA9ixa1p3z1bVs2bJ6n42bO3cuhgwZYvy5efz991Igz4qKCpx11lnYtm0b5syZgw4dOiTy/H4/NmzYsO8DEhzquW27du0wZswY/PTTTxgzZgwAYOLEiQiHwwdtn0T0n48LpkSU8O6772LEiBH4y1/+gieffDIp/6STThIXzp566imMHTsWDz30UCLiZV3t27fHtGnTDnSVmyT+bYFVq1Zp8yORSCK6Zt2/4Hfu3Bndu3fX/ov/zMnpdNZLdzqdja7fwoULtenz588HAPTo0aNRP8WKT8brTuJXrVqF9957DwDw2GOPaSO9ulyuxLu5tm3b1uD9EREREf2nis8TY7EYfvrpJ+1n4nNIp9NZL9p6vOzWrVtRWlpqLNu8eXPk5OQk0jt27Ijjjz8eADBjxoykcj/88AM2bdqEtLQ0DBkypF7epk2bMH36dPz888/aff78888oKioCAAwYMCApv6qqCgMHDsT69esxZ86cpMXLadOmoX379tptN8S+5rY5OTno06dPg7enm9tu2LAB06ZNQyAQwFtvvYXDDjssqZzNZsPYsWMBAOFwGLt3727wPonofw8XTIkIwJ6J2fDhw3HllVc2+h2dzz//PG666Sbcc889ib/a/p7Ffz4/Y8YMrFixIil/woQJKCkpgd1ux1VXXfUb1w6YOXMmVq5cWS9t165deOWVVwCg0W2cn58PAPW+Hfz000/jxhtvBLDnWwMLFizAr7/+mlQ2vnB8zDHHNGqfRERERP+JzjzzzMS3MB944IGkfL/fjyeeeAIAcMkll9T7Kfkll1yCtLQ0KKW0ZYuKihLzufh8tK5//etfsCwLjz/+OKqrq+vl3XfffQD2xAqQ3iv60EMPJaXFYrHE3PH4449PWjANBAIYPHgwfvzxR8yePbtJP/ffl8LCQnz66adJ+x0/fjwA4KabboLL5Wrw9nRz29dffx2XXnop7HY7ampqsHbt2sS7aOuKz21bt26d2A4Rkc7+hbsjov8K33zzDS666CKEw2G89dZbePvtt7Wf23viBuz5i/OoUaMAAI8++igeffTRRu9/78VBYE90ztzcXAB7vp2ampqa9JlwOJyIqFlcXJxIX7NmTeLn/126dEn6lue1116LhQsXYsqUKTj55JNx11134fjjj0dVVRVmzJiBiRMnwuFw4Nlnn0XXrl3Fetfdf/xnTuFwOHE8WVlZDfom6Pr161FVVYWqqioAwPnnn4+zzz4b48aNw9FHH42NGzfi7rvvxq5duzBixIjEz+Tj+y0tLU1MGHfs2IGVK1ciPz8/MQk8++yz8eCDD2L69OkYMmQIysrK8M4772DYsGEA9rzLKhwO48wzz8SYMWNw1FFHQSmFxYsX4/7770daWpr2G8dERERE/208Hg/efvttDBw4ENOmTcM555yDa665Bi1btsTPP/+MBx54AEVFRTj66KPxzDPP1CvbrFkzTJkyBcOHD8fjjz+Obdu2YdiwYcjNzcXy5csxbtw4+P1+nHXWWbjrrruS9t2/f388/PDDGDNmDM444wz885//hM/nw4svvohp06Zh8ODB2mBSaWlpAIC33noLpaWlGDlyJNq1a4ctW7ZgwoQJiYVQ3a+9Lr74YsydOxcOhwMnnXSStk2kd5BK9p6fDho0CFdddRVuv/129OvXDzt27MBDDz2En3/+GWeccUbiF03Anrls/B+wZ1F05cqV9ebVZ5xxBhwOB+bPn48ZM2bA7XbjhRdewBlnnAGn05l4T+tFF12EMWPG4Nhjj4XL5cIPP/yABx54AA6HAxMnTjS+z5WICIqI/uc9+eSTCkCD/t199931yt5www0NLjt58mTt/vdV7osvvtCWW79+/T7Lrl+/Xjzu999/X51//vmqoKBAOZ1O5fF4VKdOndTVV1+tli9fvs9229f+R4wYsc9tKKXUKaecktROX3zxhTrjjDNUVlaWcrvdqkePHmrSpEkqFovVKztixIgGnafx48erjh07KqfTqQoKCtTIkSNVWVmZUkqpmpoa9e9//1sNHTpUHX744So9PV35fD7VvXt3deONN6qioqIGHQcRERHRf4vi4mJ1++23q549e6q0tDRlt9tVdna2OuWUU9SECRNUMBgUy/7yyy/qb3/7mzriiCNUSkqKcjgcKj8/X5111lnq//7v/1Q0GjXu+7PPPlMDBgxQWVlZKjU1VfXq1UtNnDjRWO7HH39Ud955pzrxxBNVdna2stvtKisrS5100knqqaeeUtXV1dpyGRkZDZ7LN9Te89O7775bLV++XA0ZMkTl5uYql8ulOnXqpO6///6kdrz77rsbNK9+8803Vbdu3ZTT6VT5+flq2LBhasuWLUoppSKRiHr//ffVZZddpnr06KGysrJUSkqK6tq1q7r66qvV6tWrG3wsRPS/y1KqkW+mJiIiIiIiIiIiIvovxXeYEhEREREREREREdXigikRERERERERERFRLS6YEhEREREREREREdXigikRERERERERERFRLS6YEhEREREREREREdXigikRERERERERERFRLS6YEhEREREREREREdVyNPSDo66+Wszr3rOXNj09I0PesV2/a8tmiWVUTMxCTEX1GfLmoFSjiyAalSsRCoe06TU1wUZXorq62lAH4VgBeD1ebXpqWqpYxuVya9OdDrtYJhKLiHmA0LBKXp93OISuaDp/UWE/AGBJBeXzJ/WHPXn6chHDubCEyttscrtaYr0Bm5BnqDZqagLadIfD8LcSwwalvudwykOJ0+nU78ZwLUVihvMU01fQ1CftwrmwbHI7VNfI12BMqIPpL1DiNWjJpVxC2wFATOiwhi4k9j3DsAvjRShlmSohjNVlpRViEV+6T8yLCed9d9lusUw0ou9fsz/9TCyz5tc1Yp7Nrj+H0ngMAPnNmmnTL7zgQrFMaoo8jkeF/hAK6scAAFixolDM+3Tmh9r0Cn+lWCYUCWvTU70pYpmgoX7hsP7c2kzzBPG6kMvETJMLaZ5g2J5TuKeaBtdYRL6XRIX6RYX2AeRjMt0vggH9HOZ/2bV/v0XMK2jRQpue5csUy6Sm6+fFXrc81gvDCwBAKX0/DEtzYsh9LRzWX78AEAnJ89hIVN8PYzF5ezHh/h+JyH3aNFZ4vWnadLdHuhbl5xC7Xb62rZh8MqSpnSWcIwCICVekwy73B5tdnkNCmDvFTHNfw3xLuq8Yn5OEscc49zVsT8pTljyaiUO6aUemhwCx/UwXp3AuDLcbY/3Eua98rcvzZdP9Rq6C+NwsXEsAYBeeJb0ueV7gcsvbk+69CvIxhSP6e5sS0gEgJUU/pgBAVma6Nj3VLY83EWFMLi8tFctUBGvEvN07tmnTN24uFsuUbBPKFMllKivkuXlEmIP40uQ5e7fDu2vTu3btIZbxZcrbK6/wa9OLijaLZTZv3iTmbdiwTpteZnimqPDr6yDd5wAYF7WkPh4zDB4xYf4dMcwtTWOeEsc8uYwlTFbshjm7aeyQptmWYT1Jeh4rL5P7sWnuk9juPj9BRERERERERERE9D+CC6ZEREREREREREREtbhgSkRERERERERERFSLC6ZEREREREREREREtbhgSkRERERERERERFRLDk21l1Cg8dEuTZEXlU0qI6/hmqKDSTG7LCFCoKmMMoQplCLCAYAlRLv2NiFKpxg1HkDAECk0xauPyqwMUc1CQvRTZegekbAhOrwQ1sxmM5wLIYqoFBkeAKKGKI9SHaTI9QAQFiLMAYASotk5TNFKha5siq7sEKJJ7tmX/nyYzq3TpY+0ajdEKzWGUZYi1pkiUAvnKRySryWnMD4AcoTYQECOJile04YohT6fHJUxFNJH1vSlyVE1LaHNTQHlLUNkwagUytRwTHYp3LIxcmzjI5LHDOOuTejHzVs0F8usXb9WzJv5yQxt+uYtRXIdhLE6UCNHgq6sKhfzpBaKxfQRsQEgJ0cfKTRdiKINAEK19xDuTduK9VFRAaDY0EZeT6o2XYqADABWjf4adDjkiM/SfRMAYlF95FFT5OuaGv39Ubr+AMBuiLgph2iW+3jEcC+RmMZxaQyNGuZEUrMaAkuTRvluOYJxQY5+zHIbIiU7hTHdbghka5oHhaX5t3GOpu8cTsN3KCyHnGe39NdWLGqKjKuvX8Qw93W75GvY6ZTmvoaowtI91BDY2G64V0r3w6gpUrLAkrsQYjF57iQ9d5kue9NcWpr72g3nySH0B2kOa9oPIM+LTfNvae5kut+YSHtShvuK9Exhen6S+hAgP2tbpvuN0Mcddrm9I6bvUgnH63Ca7vH6c+Fxe8QyLuHZBQAsoTdbhgs3LBxSTVQ+F26b3F+dUt+LynNIf3mlNn3bJjli+7YKed65e9cubfr6DRvFMmUVZdr0nTtKxDL+SnnNQZrrVJXKEcm7dzpcm96iRaZYxmNPEfNsQf053GUabwyR46srqvXb27Vb3p4wsTIMa0Zup77uNsN4E4rqn0vDIXl8MA2H0nVmWouLRfQbdBnmD9J+AEBFpPuZfCN2CW23v/gNUyIiIiIiIiIiIqJaXDAlIiIiIiIiIiIiqsUFUyIiIiIiIiIiIqJaXDAlIiIiIiIiIiIiqsUFUyIiIiIiIiIiIqJaDQ4lVVouR2qrEKKuOdwusYzLqc9zmSLtSRGeAdiFiFnKFIJaiOQcicoRKGOGCIamCOwSaV+miJGmCGVVfn10t2BIjtwnRedNTZWj0jns8nmSIrqaomrGYvoobnabfM6jhuiGMeGYnIY6mM6fFLnS1FfslhDV3tCHjLFMhSh8pgi6lvA3EcvQruZu3PioeVIZuyHcbECIeggALiE6pakONiFiqiGYOzyGyN7SMZnOrHi4hvNnM0Yr1beRKXqgFPFeah8AiBkij0pdOWq4LmqC+kiOH8x+XyyzePFCMS8oREVXYlxbwGrCteRyyPezqip9NHdntlzmhBNO0NfBcC78fjnyaFFRsTZ93dpfxTJSRGUAcLv0da+sknu5dP829YdASI7AahPu+W6XHF23RugP0Yi+3wHm8TA1xaffT3WVWEbqRw5DHwoEDe0gRiY2RR7VixkiYlOyiGHuZHfr+7vTKV/D0Zi+H9rshrmlJfcb6a5jGfqGFNXecsjjQTRouBcJ0XnthijmMWn+LcwFASBqiGyMmP76Mc3RAgFhrDDcO3wphnmxMGeImeaJQiRnFTQ8Ayh5e4gJ0eENc99I1BBlXbjJWzG5DlI7mJ7hTFNSm9BGlmEOKc0HbZD7UFSIKA8AMaEvG27X4vwyYnh2adrzgSHKtNCVnYZ7kekRQAlzUqfwTA8AUeF5VhnuReGw3P+laZrDIV+3NqH/S/McAIgZnsODwthRVV0pllm95hdt+oKvvxHL/LRmtZgXFs5FdUC/DgAASphLREPy/EgaqwEgGhbuZy7DOOlJ1aa7LX06AJSVy/Oj4m079GXKSsQylX55TQs2/Xl3ueQxVHruktZXAPO1Lo3XluEZxRnTz4vtwjkHDM+lAGDp2yEkPMMBQEyon2kpznRMlqXv48Z2Nd1M9gO/YUpERERERERERERUiwumRERERERERERERLW4YEpERERERERERERUiwumRERERERERERERLW4YEpERERERERERERUiwumRERERERERERERLUcDf1gZZVfzItGYtp0FVOGMlFtesxhF8vYlSXmwS7kGcqEwyFteiikTweAaCwi50X1x2Sz5HVpS8iLQt+mABAMBOXtyTsSy1RWVAr7qRHL5Oc1E/NCEX0b2U39QWhXu03uD6Z2lRrCbpe35/F4xbwqv77/h8NhsYwSTqHlMv2dwnRJSudQ3l5M6dtcCX0fAGx2uQ42m74O0rECgBLqbRnOrcNwnkJBfd2dTpdYJlij78t2h3ys4ah8bt0ufV+JGMpI/dXukK9Nm6EdLHFsk7enxBMll7HkyxYqJozjQr8DgFcnT9am//DDcrGMy+sW8yyh7r6UFLFMRBirg0F5zMvLbS7mZWVkadN3l+8Wy1TXCGNKNFMss3t3mZi35qfV2vTlhcvEMg6n3P+rhXt+1HCx24RrOir0EwDwOD1intQvDd0LTqdTm+5LzRHLBMPyPVXi8cj1jsb0beQ13GNMbSTdtxyG+ZI0TgaDAbEMJQsGqsW8aE25Nr3aL489Ho9+LKsxzROjpjmp/mKIGQbuKIRxW5i7AUBNUL5GokKfstn11yIg33vDIfkeWlMjnwsltJ8SxnoAqAno6223yeOi1yXPM6TrVBkGrEhE366xqGGeaNie3aFv8xRhXAQAp1MeR4LCXDESlftKLKwf/0zjldMp3+PtQjnTuVXCGByzy+2qILertD3Tc640N5Huk3vKmCZc+ryIkq+ZiPCMYniahsNwLpT4LGnok0IZm/TcDsAyPAPbhNpL+9mzL/0x2Q3PT8qwfhCN6I93u2GOtnTZSm369z/q524AUF0lb8/h1d9nnG55buJ06cc2yyOPay6h7QDAJlwXUHIfz8rM0KY73PK4W15cKuYVrizUphcVbRDLbN+1Q8wLR4RnTMPzok0YoyJRw9hvGL+k53ppbAWAmDAW2YVzDgCZafKcVAl1L7cq5DJCumldwbSUYxPWSyKG+bLDpi8jzx4aht8wJSIiIiIiIiIiIqrFBVMiIiIiIiIiIiKiWlwwJSIiIiIiIiIiIqrFBVMiIiIiIiIiIiKiWlwwJSIiIiIiIiIiIqplCsldjxRRHpCjSYcjcuQ+KTp8jSGCq9tliJQc0UezM9W7qlofMysWlaOQRQ1RzSJhfdRIr1eOQuYRotzVCBGUAcAvRGwHAEsITOc2RD2UondHDBFTTVE/pe1FDduLxvR5TrccuU+KZAcAbrf+eL1CewNyJE4AcAl9zxRV0yVEJZWiOAOAU4hwCsiRbS3DuRADWhuiP5rOrRQQ0RRzMyJcgzYhkh0AKEOEzIgwrkQN1215hT6qn9Mlt7fHEGnSlanvl9GIIXKfcG5N7WCmP0+m82eJ+zJEZjWcW4cw4KxapY8GCgC//LJGqIFhbA3JEZpTUnza9JYtW4tldu3aqU0PG6Klp6eni3kel76vOJzy+PXD8h+06TnZeWIZh0PeXnauvlxGWpZYZnvJVjGvvKJMXwdDtEu7MLbFDPfNmCHaZU52vr5uZbvFMlL/jxn6V05OrphnE66NklI5ams0pu9HSsl1yDWed32b2w0Rn0t26/t4RmamWIaS7S4tF/OqqvVzsbyoPI8NVOvnOqFgjVjG45HvRVIk+qgwHwWAmqD+HipFRAeAqGG+JV3DhoDysIQ+bVnyvcjvrxTzpGjl0rUDAIhJEcQNcyrDWBYM6dvIdC6kaOCm+ajpmKTA43aXvD23Q+5fVlC/waCQDsgRox2G+RZs8vbCUX37KcO9Q3oOMc62DNOgmHBfiQpR6PdsT9igoRJSPwaAoDAPqqyUnwmrqvTXjMsQOTvVlynmuTz651nD6YNdmHeanl1M9zaxjxvGDnHqazgXUUNEcih9wdWr14pFvlqwSJteWinfY7Iy9fNbAPCk6J9nTc81Dpv+2ow2ce7rFuaDlZVVYpmdQoR6aV4OAFWGNRFl05/3iOHZKhiSx+SqKimeujzeeNL058JmfH6Sr0G3V7/mUFMlzxMs4YHfLi0MAXA55bE/5hTuqYa5ivSM6fHIkwGb0CdN24uGDc8UwtgPw1yuIfgNUyIiIiIiIiIiIqJaXDAlIiIiIiIiIiIiqsUFUyIiIiIiIiIiIqJaXDAlIiIiIiIiIiIiqsUFUyIiIiIiIiIiIqJaXDAlIiIiIiIiIiIiquVo6Aerq6rlvEq/Nr0qJVUsE3Dot+ewOcUyIVdAzLPZ9IcSjYbFMsGaoH4/4ZBYJhKJiHmp3jQhR4llagJV2vSK0nKxTHlZmZgXica06XaHJZbxerz6MnZ5Pb26Ru4Pebn5+jLVchlE9W2Ulib3oaoquV09bo823eGQj0mpqLw9r1ub7va6xDI2m35fht1AKfmYLEt/Di3I59YmnMNo1FAJQ3+NCv0rHJavi7BwPdlscr2lYwWAmKGNJDVCfw3UGAqly1nRqP5atzvsYhnpkIznXK4CpGIxpT9HAGBX+i0qyGWUUMaUV7ylWCxTXa2/Xzhd+msMkMcUAKisqNSmr1u/TiyT6dOf3JwseT/hkHxfyMnJ1abbdpeIZUpK9HmbNm0Sy1T59W0HAFu3btGm+2v07QMAwaB8TxX7V0weO9x2/bhr2eXrwuGQpyFuIS8lVb4vBMP6+3o4Ko9R0Zic53Tpx3iXQ56rSNKEfgcAGb5MMS8qtHlmepZYJtWTok03nQtKVlleJuZV+PXzt5qIfI1EI/pxxJKHYKiYfI9wOfX7qgrI41WFMI5EDfW2GSrodOuvkYjh3hYR5oOmZ43ScnleHIno6+d1ydepy6UfXxweuYxTKAMAbo9+XqAMY2ZYGK/sdnk/0pgEAB7hXDjt8jFZwlwVAFwu/Zju8cpjsM0uzTPkuUQ4LD+rQZjT2C253jFhbmJTchnL8MwTDOjvlYGQXG+78J0kaV4OAEqYYwNAUJpnG+bL0iwyGJTHB7dXvh+6hEvabpqtCs93dpd8L3IKfQgAIkKbh2Jy2zmkPm5qOsN5grBWUWV4zvXX6B843B79NQaY58Uup/5adzvla90utYNTPhe5OfI8Q+rjZeUVYplf1urn5r4MeT/hgH6cBIBIWH/enQ657ZyGNrfV6K/1kGH9xy5cg07DubCEdSsA8KX59NszlAmJ4658XZjGPKlHOF36NSMAcHv0be7L0B8PYF5rki5PyzC3EIYbbNuif0ZqKH7DlIiIiIiIiIiIiKgWF0yJiIiIiIiIiIiIanHBlIiIiIiIiIiIiKgWF0yJiIiIiIiIiIiIanHBlIiIiIiIiIiIiKgWF0yJiIiIiIiIiIiIajka+sFgMCDmBYS8YE1QLBNTsYbuOiE11SPmuVwp2nSbzZI3aOnznA67WMTtdot5DktfzhL2AwDBkL7t/FVVYpn09HQxDzFhX4al8XAorE2PRuRzFArrywBANBbVpqekpollSkt3a9OVWALwpfvEPJdLOE+GcwEl59ns+jzLkhvWgr4/xND4vg8ASmhXZWol4ZCUMrWs3A6RSESfHjX0h6i+3pGIXIeYcKwmNpt83ebnN9PvJyqfC58vVcyT+pdpXJPaXBn6XRRyO8SEdjWeWmF7sZhc75jhPDkc+ltIbp6+vQGgWW6BNt3ulK8l47ib6dSmZ2TK46RPGEOrq2rEMpmZmWKedG53lWwXy3hT9Me0ceMGsUy1X74vbBDKVVXLZUx9RRwjhPscAGRl5GjT7Xa5TFW1X8wLCeON0+ESy/h8mdp0w8gPh02eCpWXV2rT3V6vWCY/vYU2vWWrVmKZWDgk5tmE6ywzO1ss4y/L1KZ7U+V6U7JKf4WYV1WpzwvUVItlwiFhrBXGcwCIQX8dAIBLuBZChnE7xS1cPx7TXFUeG112/djtcMjbqxaeD0Jh+Vg9HrnvOp36+4BluPLDIf01Vy3MiQGgwi+f2yyn/hnF7dbXDZDvvQ7Tc4jH9CwknFvD/Mg0b5Hq4XDKYzAsfd8LRQx93HAzks5g1DCfDwvPKBFDOzjs8n1AmipK81sAiElz86jcx03PXUo4Ty7DdWET7r0qZrrO5P7ldOnbyCGMAQAQEeeXhmchJW9PagebYS5tCfOWqOEZQFlyXlAYI1xu+Vy0KGipr4Ph+vN65LHD4RTWHMQSgMOhb1evV55j+9LkZ21prSJgWP+R1owq/eVimZ3b9WsEALB+82Z9mV07xDLlZSViniX0y1SvfF3kZ2dq06OGsxEMyGNHNKLvX07h/AGAXVgjM30z0jTmSfcmtzR/AJCWpn9uzsvLF8uY7mfS44bN8BwSFubSK1cUimUagt8wJSIiIiIiIiIiIqrFBVMiIiIiIiIiIiKiWlwwJSIiIiIiIiIiIqrFBVMiIiIiIiIiIiKiWlwwJSIiIiIiIiIiIqolh8faS01YjnhWUamPcutJkaOLSpErTREHwxE5iqzLpc9zuuQIcylCxLNYVC5jikgejOjbyGnJ25Mi1Kd4U8Qylk2OutaubVttuscjb6+mRh/9NBCQo6LGYnI7VJbrz3tWjj6CMgB4hKhrliFKocMhR1azi5Hf5HoruyG2oBR90RDZM2aKACkw9399/zJFh7cLx2s6f7GYHCFWjKZqiLZtCZFMTccqRbwF5IjpSt4c7EJkQZvhWrILkalNbIa/QYWEMVRqnz11MP1NS18uFpMbIiJEYA2F9FErASBmiCLqESKFZ2dmiGVOOvEkbXpZeZlYJhqV+2Q0pm+H3SVyhMxt27YJ+5HbLjVFH/0RAIqK9VE6dxsicXbq3FmbnpUpRz4vLzFE7Pbr78OmaJJOpxwZ1eEQok4bhknpvpWRkS6W2b7VEClUGEPz85uJZaTq7d4tR1lt176jmFdZpo/cGjBEtZci0Zr6V8tWbcQ86Ro0RdK2ZehbIlWIYkp6NsO9MujX94HSkjJ5e5YQUd5wLzKNz263fh7kMsz5fD59HwgboncHA/J9ICJEJFeGwSIqlJEiFANATk6WmNe6tf76MUUBrqzQj6eBarm9IxHDHDKib7+YIYK4NJ93StHuAbgM47bYeoa5qinysnQKTX1SmgYpQ8Rom2GqEwnr29UyRFKXxkZluJ5DIfk5VxqD5WcNuYwy3AfshnHAsuvvyU7hXg0ANmGOZjc875iOSbzDWob+JexLGeaWYUMb2YTOYprPV1dXa9MDAfmcW4ZnK2manZ0jz9+O69NLm767tFQsE4nI15l0Pfmr9HNBQI4gHjGci3J/pZi3tVg/z96+c6dYJicvT5ue4dP3VQDYXS6f25hNf0xuj9yP09Lk+6N0z083zJ3Sffo5rum5tAL6PglA7GBer+G+4E7Tppvm+ZbdMIcUmtxfI9dbum+lGZ6fvGnyeXd79PMb0xpBKChf0/uD3zAlIiIiIiIiIiIiqsUFUyIiIiIiIiIiIqJaXDAlIiIiIiIiIiIiqsUFUyIiIiIiIiIiIqJaXDAlIiIiIiIiIiIiqsUFUyIiIiIiIiIiIqJajoZ+MFATEPN27dylTfd6PWIZtzdFqJC8hhsKRcS8SLRGm57hdIplbHa7Nj1QUy2WcblcYp7dEvalDOvSlr4OsZjc3s3zmot5KampQh3kKrg9bn3VDNV2OuV2CAT0dXfY5e7mdnm16TZLLuOwy+dWKeGALbkhLDFHFpP2AyASier3Y8l7ikVjYl4wGNKme1zydSZtLRINi2VUTK6DzabvFNGIfG1GY/p2sNnldvAK4wMAOBxCnzCci1hMn+d0yf1L7EMAYkp/TMJuAAB2of/bbPoxYE8l5CypL8eUfP5CwaA2vbyiQq6CoR3Kysq16TUBeQztcFgHbfrmjZvFMj//8qOYl5uTr013OOQxyhbW91dPqn4sBIAdO7eLeVuLi/QZhvNXWenX18Er16Fl6wIxz+7QX0+WYSCvCervmwAQCOjzNhfJ58kujA+hsDzetGuv7w8AUFVdpU1v3kK+BzqF+0J6RqZYpk3rVmLeFuHOUFAgn4tt2/V9xeWS71k5uTliXrBKfy7sbnn8ysvXXxdB4f5Mert2l4h5O0r1ed4M+f6V4tXPdVJS9ekAoIKGeYvS90+HWx7/qqr011XYNMcO6+cfAOD06PthLKS/TwJATBgTHIbbYWqaYV4gzKtihrmJT5gvZ/oyxDLVwrUIABDq4HLL5zYa0bery3D+HMJYDwBhYQ5pF5539uxLHkciIX39ohH9XAIA7Db99uwOefwLGyZPYWHe4ja0kd2pvxdFDPPbQMhwbiP6+tkMN/loVN//XdIcFoAv3SfmWcLzUDgq93G70CcdhmdZ0zEFIvrr1mZ6gBLmqjbD/MgyzIsdwjwjbJhn+Cv0860aoW8BgEN4PgeAGuG6cBueWQ9rp5/rFHu2iGU2b9wg5oWEc+E0PM3GhPtFsEbu+1Vl+rYDgOItW7Xp/mr5GcBm158/yy7PfVNSM8W89i3b6zNay+2ghHEXAHbu0t/XSw1zgVBY35l9hntJWka2mOfy6J/rXW65jRxCu8YM4wMMz+HSmk3EcJ3ZhBt4Sqp873YajklsB8PaXiAk129/8BumRERERERERERERLW4YEpERERERERERERUiwumRERERERERERERLW4YEpERERERERERERUiwumRERERERERERERLXkcG57CQsRvwEgKESL275zl1gmO0MfOSwzN1csY4pQn5Gerk03RaCWIrBnZGYaysgRxdxCJExTtHkpAHVIaFMASPfpj3XPBvU7U5YcGVIK5RwxRBc18aboo5pJEZQBwBLyYkKEdQCIKrl+SogUauwPQoS5PfXQb0+KggkAEeGacRjCwJoinFvCuTVFzZMinIdCcnjKYNAQDdepv2aihsijNuHcut36fgKY20hBvy9laDspeq2JMoU4FyJNwlAHh0PoX0IEUQAwNCtiQlTZqOG6tQvRWUt3l4llvCly/6qp1kfcLi3bLZZp314f0bJTl65ima8XfC3m7RTuM16v3L+KtxZr05Vq/PW8p5w+3WmIChyLCNGMDZFZ3R75XJxw4kna9Goh0jwAhMNyX9lWrI/cunOXfF93CxEtnYaIltnZcnT4nBx9nkMYhwCgoKU+4r1j82axTFZ2ppinYvrrNr+ZXG+XVz9XsQyTgXRDdGT40rTJNiEaNSD3ZSnqNemZ4q36hYjp1QE54rBNiHDuCsjXvd3Qb9xp+msuxavvMwAgBUz3GMYXxPQR5QEASt9KlhCpHABSffpKuDzyPN8jzC0BwCVcCyFDFGwpenA0Jp/1UEB/zwMAhzAXsxnm35YQXlwZosYHDVGApWIOwxgcCcn3NilCvcPQJ6VozWHD/CgqzNkBwC7U3XRfkbYXM+zHYZgnKpvpGUrPKZwLl0uut90wplvChSu1N2B4RjGcC+m5AYDYwaKGKbbUrKZ5vl0apCCvR4Sicr0jwpy9ukaO5m56FvJX6CPHOw31zhbmM1mGaOlrqn8S83aW6KO2W4Z5bE1Yf0zBsDxOGh5zERbKuQxzX5swdpjmvq0LWhvy2ur3Y1jhCtXI8+KiIv3cd/VqQ0MIz4umuarPcN49afr7bYpHjjaflqJfgzK1gzJcM26XvmAkbLj/CM+z0hoPANiFOREAOB36e77LLc8TagJyX94f/IYpERERERERERERUS0umBIRERERERERERHV4oIpERERERERERERUS0umBIRERERERERERHV4oIpERERERERERERUS0umBIRERERERERERHVcjT0g4FgjZhXVlGuTc/OzpF37HTq0212sYzX4xHzLEu/9mt3yttzCnVITUuV92NYY3bY9c1p2ZRYRsX06V6PV66DXa6DZQn7UpZYBtDneQx1iEWjYl4oENKmm86FTTikmNA+ABAKRcQ8p0O/L8smt4N0LmpzhXS5kN2u35dlOBXRqHxMqWkp2nSboT9IB+VyucQiNTUBMc9m0/fxjHR93QAgGAo2pmoAgGhUzgyHw0KO4Vw49Ne6FZbb2zKdKLmUmKOkSzMmX0s2w3hoE/qyTbqYAAQC+nNh+stZNGK41oVzm+qVx9D09HRtutebJpa5cMhQMW/T5o3a9Llffi6WqfBXaNMtwzhpF8YUAHDY9XmpKfIxHXlkT216i4ICsUwkIvdXh0N/bfr9lWKZ1FT5POXk5WnTTz3pFLHMug3rtOkZGZliGW+KfJ/Jy9XXwV8pH1OaTz9P6NS5nVjGsrvFvGZ5zbXpwbD+PgcAsZj+Ync45SmXMgyIKR79eTKNUTUB/ZzNdA+kZJGQfD8MK/29qKZaPy4CgNclzE1S5Xtoile+Rjxeoe8a5gUOYW6XathPTJwDAdGAvo3cafKc3SnUzxLm0QDkiSIAu1C9FEM7hIL6a9g0BxLn2ACcDuGYDJecdNUrw+RXGeYZ0rOQ6SZvms9L9xyPYQ4JCPdKwxjncshjsHRIbsN4Ggzqz2HMJs0fAQuGuZgwn/earhlpPmF6rgnLdXBZ+nYN1lSLZaqr9e2QnZstloka7hGWMA+S5kAAoJQwb5EvJUQNfTIgPANEo/IGpevC9KwRMtzjpRZyueXrIkuYB+UI8xzA/Aywbv2v2vQVy5eJZbZu2aFNj0KeW7pN6xFCSxQ0yxfLdGzfXpuen2tYM3LJc1VpLhYQ5kAAYDfMOwta6Od8EfHZEwgKeV6PfF/3ZeifhQDAJZRzGMZdT6pPm55ueD53u/XPxgDgEsbdULU83oSFfmQ3LTdKOwJgs6R1NbmM0ynfv/cHv2FKREREREREREREVIsLpkRERERERERERES1uGBKREREREREREREVIsLpkRERERERERERES1uGBKREREREREREREVIsLpkRERERERERERES1HA39oM0hr6360lK16enpaWKZ9MwMbXpKSopYxuP2inkOl/5Q0lLlOng8+u057U6xjGWzxDwooYxlWJe26QvFYsLG9mTKWTZhX4bNWZY+0+VyiWUCwaCYV1NdrU332uTz53To29zhMHRRw6lwOOxCjnwuFOR2VUrfRnZD/SyhgjbpHMHcrpKYqT9E9XnS8dSWEnMcwjhg2Q19XNqV0O8AwG6Tzh9gCd3y01kfi2WkceC4404Uy9gMx2Sz9PWzG8ZJJVzTlrAtwNwOMaU/T6Zrxu3Wpx/WuZNYJmjokzZhbDMNedIYLxwOAKBnn6PEvFZtW2nTV69ZLZbZVbJTm24cqyNyltulb9iTTz5NLHPSSSdp003jQzgcFvN2l5Ro02tqasQyBQUFhn2FtOmxmNwQnQ7rrE3Py8sXy5RXlIt5GVn6eYLH6xHL+FL1ZQzNCrtTvufbheszViWPX3l5uUIdDNezYRx3ufWDXiwqnwvL0m/PbssWy1Ayy9BxvE59XlqKfJ5TUvTz5YxM+by43PK82GbX942oYQ5pWfp7hNMl7ycai4p5yqHPs5RhrhPQl4nE9OMOANgN92SnMOdzu+Rr2+3VzwvsNsMzgCWPp9Go/piiEXncls6FMvQ703glTYtN/cFl2JfLpR9rTdeFPM+WJ+2mKWmgOqAv4zFMGoR9GYZZxAyVSPHo7/EpXvmaqQ7o505Rw37s4rMLULq7VJv+w/LvxTKBkL5PnnpKP7GMO01+VrOEc+syXGfhqPCcG5HHFLvNMI8V+n9EeJ4GAJtPf63b7HKfdBjqIJVyGJ5r3G79teQW1iIAIO/Y48S8tm30c9+tW7eJZdau26hNjwnzBQDwCucPAFJT9f2/59FHi2VOPeVU/bbS0sUyZeV+Ma+mpkqbbngcg8epvw8DgArrjzcnR57H2oQ1KNMznLTuAQBpmZn6MsKzBgCkCmOUz+cTyxgf3cPCuOuWr1unpT8mu12+lmyGMQ9C+0WFtQ0AMC2f7Q9+w5SIiIiIiIiIiIioFhdMiYiIiIiIiIiIiGpxwZSIiIiIiIiIiIioFhdMiYiIiIiIiIiIiGpxwZSIiIiIiIiIiIioliEEeX1uQ+T4rAx9VNq0NDlCfVqqPkJZphAZDAC8QnRlAHAKEfpMUcjsdn30LcsmR80z5UlRqy1DNHcpnJdpP6ZwktGIPmquMaKlEBnaFB27qkqOWBcO6culpslR6aSo9tI52jchenfTmhXhsL5dXW5DFEWhXU0B3DyGCHhRIaKkKVqcTThgaVuAua+EQkLkbEOI89IKfWRPU4RnYyMJUauXLy8UixQ0a65N79TpcLFMerp+XAMAj0ffRqYovjahLyvDwZoiZ0vb8xjGPI8QXNx0XaQK0UUBue8pQ73FSPR2uUwwIEcZrqio0KZnZMrnz+3WRyUNGca8qJL7a2aWPsJ1+47txDJSM5h4vHI01WbNmmnTs7Ll6NtutzzeSFFqs7LyxDKZGUKUU8P9zGYIZSodr9fQDt4UIc8QsdsyRLaV7sUeISIpAITD+v7qTREuQJjH3ZgQfVsZIo86hDy7XR/5lPRM10hmXo42vVUrffRiAPClZ2rTM3z6bQGAy9DXHG79vFjJt3g4hWOyG+YfdsjjnwX9zuyGPq2EOYMyDIxOp9zfpbli1HAvisX0xxQyRLX3B2rEvKhw3ftscpTiVCEiecQQUd7hcsl1iOnPRVh4NgAAp8MwjzU9i4j059BpqHckoJ9b1lZCm+xwyfeBqNKfC4fQVwFACf0BAJQwSSr3l4llirds1aabIkaneOVI4Rs2bNKmr/xxtVjG5dTfc3aW7RbL5LtzxTypPzhd8vO5PaK/v0YNXcsUoV4JU9xwWL7WHR59/XLS5WszFJb7ZCys70dul/zMGgrp+6QSrlnAfI+PKX0D2g1LO2mp+uONxuS5r2EogiVEMc8X5qMAYHPq7zM1IXkeZhqjMjIytemm5QMpmjsAcV3GZpcbIiNHP8+Wxg0AiAjP0wDgTdOfJ49bnkNKc1Kb4Xk6Zlo/EMZr0/Od0B2M9xFlNf7+Y4vJbRdtysNVA/AbpkRERERERERERES1uGBKREREREREREREVIsLpkRERERERERERES1uGBKREREREREREREVIsLpkRERERERERERES1uGBKREREREREREREVMvR0A9GlZIzLUubnOJNFYv4fOna9NSUNLGMw2morqVf+41GY3IRYb1YqahYxgb9se4pKKw/m5alpSKG5lbCsQKAzaavn+mY7A59u9bUhOU6xOQKur1efbrLJZZxCHWwhL4FADFDHRT0ecrQj015TrHvmU6uUHfDfiIx+TyFQyFtuqEZ8POaH7XpW7YUiWWyMrPEvGAoqE33evTnHAACVTXadLuhHzvdHjFv645ibXq/E/uJZXJzcrXpu3fvFsvk5eWJeR6PXL/Gsll2Oc/W+L9pxYzjl357EcM4CeFaAoBIRL8v0+3C4dRfF7GoXG/TOOBwOLXpgYC+rwJAs/wWwrbke8zWYvmaKS8t16av/mm1WOawDp206RFDO5jOhU2oe4pT3z4AYBnuZ63bttKXMZwLqb+azkV2draYJ50Pu00+T9I4LtwaAezrmPTXp2nMc9j1bS711T2VkLOk+62hCGLSXMB0w6AkhjMGRPRzpLCSx1O70DdMZ9My3CsdDn2ezTBfDof1Y0y4pkosY3fI9bMLfc1tl+9tDpv+HhqJyvNO08hoh35fsYg89lSH9XOTcFiug2kcsbvd2nTTfMYpjHHK0IdUzNBG4vUtX/fhiH5uCQCW0BZ2l+GYnPpz4UyVn++CwTIxLxzSt0VlhVxm1coV2vTt2+T7eKhG3x8AIEV4Nm3ZqkAsU+WXrif5ulCGx3JpvtqiVXOxTLNm+vrFonJ/CAQCYl5qSoo2PRyU+5DToT9eeSzcx7N7TH8R2mNymZhwzVjC/R0AlLAfAAhH9PsKhw3XkqVvc4dLPudR4bkPAErLy4QdySNlbr7+WSgaM4yTVX4xz1+t7+MK8rmo9Evbk+9zXre8fuBy6fuR3fA87UmRt5eTp38GTo9limVS033a9GgkIpYJGK4ZmzDHtRnmAlHhvh41XBcuw5zU6dCP8YZbk7zWZJgLmCay0nOhTVpvg2m9Zv/wG6ZEREREREREREREtbhgSkRERERERERERFSLC6ZEREREREREREREtbhgSkRERERERERERFSLC6ZEREREREREREREtRocSsoQRBapbn202PRMfdQwAEhN00ccdBoioVmG0PFStN9QSI5QJkZlNkXBNEX6EqOiyyWcQnQ3U7Rmy7BBKXK8ZYjKKEVWc9jl9fT09HQxT2ojU+RsKaq9qe1MfVKKemyqQ8wQUa8moI+eaYpeK0WONQUp/nXtWjFv3S9rtOkOp3zNfLXgS216oLpaLFNeqY/4DQAFzfXRxa8b9TexTHW1PuLmlqLNYhmbU27XmBCdMi83RyxzWKfO2nS3Idq9zS53sECNPqJk1BC91rL014XNEHbXaYhwLkW7lqKE78mT6yeRIp+bmCP86q+zSFgeq+2G8dAjRCvvd9KpYpltW7do09u0ayuWKd68Vcz7fvl32vRjjuktlolE9ccrRU0G5IjtgHzbEqNWwjwWQem3aBmiZUvjrqkPGe+pwvachqiypnFc0pS48ZbpuhXu66Z2MF23UrvGYvI1I0WplcYN0nO65THYLsyRvIZx2+PVj1c+X6pYJmKIOBwK6++vsYghwrMQnTdiuBY9hnaAEP05KkT6BQC7Q992xnkd5GvbJkRmjxrmsRCCFNuEqN4A4PO6xTy7ND4bDioiRDAWpgsAgKgy3CuFccntkueJoSopmjsQCOrnvqZhxC9Ehy/fIkeoX7d2vZhXVqqPDh+okaN3F/6wXJseDMvRwE0jY4uWrbTp7Tq2F8uk2vTXTEVlpVimorRCzAsG9PO3Xr2OFsu07dhRm26ao7ndcuezCa1UZXhucAtrBC673CdN0eadQmRv07NxTY3+mceyG6KEG8Zxh0v/7BAy9K9YRJ+nIvK4Zpof5eU106Yf27evWObokL5dU336cwQAW4rl63bD+k3a9Gb5zcUybm+KNj0SMUSNN4zjShgPQ2H5eccRk9vV4dGfd5fpO4bC3E4a3wHAMIWE3dKXsxnWHKSpecSwqGUX7psA4BD6Xtgwx5aGFVO9I4bthSP6c2tcTxLmI/uL3zAlIiIiIiIiIiIiqsUFUyIiIiIiIiIiIqJaXDAlIiIiIiIiIiIiqsUFUyIiIiIiIiIiIqJaXDAlIiIiIiIiIiIiqsUFUyIiIiIiIiIiIqJajoZ+0G6TP+pw6vPsdrmM0+HUpluWJZaRc4BIJKpNDwSqDKX0W4xEI3KRmJzl86UL29PXDQAsm37N2mG3i2WiUSXmxaDfl6XktfFwRDpeucWN9YvpG0kpud42oR1spv5gN6z3C/tSSj6B4bB83ivKK7XpXq9XLLNjx3Zt+tbirWKZUDAo5nlcbm16Xn4zsUx6mk+bfvYZZ4tllheuEPOyMvTbi4h9CLDZpetMPheWYXsZ6frrrEOHjmKZNF+aNt3QJY39NSicp507d4plUlNTtOlu4bwCgMct59mFcdc0hkaFNo8ZzoXb7RHzLGFAVMbRWs9mk8cU0zHl5OVo09Mz9P0EAFq1aaFN93r15wgA2rRpK+Z16nKYvg6Zch1kTfw7pqXvr6ax39Cs4vZMpEvG6dTf7wEgZrg/RmPC/cxQcZul70fKcPM2bQ/CMVnCuAYANtX4/t+U+6Opr0TDQrs2vmr/03IzssS87NRMbXq6T58OAGke/ZjuTZXHWdOcLxgIaNOrQn6xjIrptxczjMHhYEjMk/qnaY4Wi+g7osPpEsu4nIbOK4xXEWEMAYCIdG2L1xsASx7L7EL7hcPyvE4alZxOw73fMF7FhAtcSQMZgGBIrl8wrD/vwYDcH0p27NKm+2v0fRUAqv36OTYAeDz6PuF26eejANCiQH+P9xjm7P6qajEvJjzzeLzyPd5mD2vT00zPVpZ83sPp+uPNy8sVy6QI442pP9htcl5FeYU2fffuMrGMzaFvV1+KfC5Mz5gRS9+uMFzr0hqGMpQJBgxzIKF+0toGAESF69b0XGoai9KE/nBY5y5imWBQfw16vfK427JlSzGva+du+u2l6p+5AHlNxLT0otxy/Ww2fV4kKo83VTXymCetYaT4MsQybpdQB8OzbEi4dwNAVJhDGk4TbA59n7QZnu+k+QMARIX7mdQ+AGAX5t+wyWOeUvI1KF0apucGWIaFuv3Ab5gSERERERERERER1eKCKREREREREREREVEtLpgSERERERERERER1eKCKREREREREREREVEtLpgSERERERERERER1eKCKREREREREREREVEtx4HYSCga1aaHwyGxTDgc1qZbNnkN126zy9sL6bfn99eIZdJSvNr0WFSJZdxOl5gn1d1rKGOzWdr0UER/PAAQjcbkOkBf93BYf44AICacP4dTbu9QyHBuIxGpcjIhz+3yyEXk04SY0A7KVCYmt2taWpo23eGQ2yg9PV2bburHwVBQzNu4cZM2PRyTz21Y6Ecej1ssY8rbsWuHNv3Nt18Xyzid+uuiQ/vOYplWWW3EvOZ5zbXpaen6cwQAwWBAm24znAvLkjus1EbZ2dlimYhwLtIzMsQy0ZhwLQFQwjgVVXI/lsYbp9MplineWiTm2YX+36pAPn+WUAe45HrHYvK5CIf110zMcF2kp2cKZeQ6RJR8LnJyc4Qcud5KGMBMw6Qp15L+/mncoHy8Sihot0x/ZzUMsAKHoe/ZYkIfN5wnu3AfthmmOzZ7449JbG8Alk24/8jVlq8LAJbQDqb7mSWcP9N+KFlFZZWYF4jqx/RASH+/AQC/dI/3V4tlTH0tHNTPcYM18vZcDv3cNxozXQfyeOrzpmrTnS55LhEM6NtI2eXrNGSY+1YL56kmILeDw6mvn8Mhz9lDUfk+EIno58VR4fkEAFxOfRm7W66Dwy7nSXO+UERuu6iSz7tXOLcOw5gZDurr4EzVbwsAqoT+AAABIS8SkfukSzi3R3TtJJbZtEme6/zw8y/a9G8WLBDL7C4t1abnZGeJZdq2bmvIa6lNz8iU575Ou/CMaXqejsrPdxHhtNs9+jEFAJSlv6YdHrk/pHnlZ78qf6W+bobrzJeZok2vrpH73fbtW8U8h1t/vC2a5YtlXMJzg5KemQHEhHs/IK8FuNz6YwUAu0N/LqT5KAA4XIbn3Gz9ebIMz8ZKuGydNvl+YVPyvMUl9GWnoU+GgvLxBiP6PhGokdeTpDUHu2HOZzPNpYXJommGLa3/wDDncxrGful50VQHu1jG0L+EMQoAbMJ9MGJag4oenDkuv2FKREREREREREREVIsLpkRERERERERERES1uGBKREREREREREREVIsLpkRERERERERERES1uGBKREREREREREREVEsOR7kXKcIzIEegrqqWo1PaHWXadLchqqYpkrMp1q9YByGyWppPjs5nqp+SIvcalqWrqvRt5HHL+6kK+MU8KWpkJCxH4ZOaqKxcH+ERAGoM0eI8QmQ6X5pPLJORoY8o7zBETLWEyIuAHO3aFAU7LEQ43VMPfd+Tzh8AlJeXa9NDQSFKLszXzNp1a7Tp23fI7WoJUfgChjqUlsnnfWXhCm16ZmamWKZ5swJt+orl+m0BQFWV3L/atdNHEV29Rt8+AOAUIkNKfRUwR87eXaJvo6pqOaKykkJkG6JT5uTkinl2lxDtUiwB2IQxb/s2OTrs2l9/FfO8KfponLm5cr39fv34FRUiTgOAzXCtu4UoinZDJGEpdLxNiLC+Z3um8UYI+2kI1iifdkO0dKvx0R/NRQyR3ptQBylqqykaqKldbTb99uyG8yT1cSniJwBjIykhFL2xWYWIrkoKDwtDH4Ic+dpIqLcyRN2lZJGYPHcKBfV5NQF5LmH59ff4WFju026PPPeVIuDGbIbxypIiGMt1iITkOYMzpO+7UcvQdmGhjOHKCoXk+VFImvsarqtgtf6YyoVztKeMPDdx2PXtmpEuR63OytTPfW0uOXp3xNAdwsJ1LwzNAADTkBCK6tuvpkqe65RX6Oe+NsN8KyzsB5CfRUp27hDLbN++XZvepn1rsczmLcVi3qoff9LXoaRMLON2658l3Q75BJbskI/JYelPYpUwpwKA1DR937N75XPhcMhzp/IKfYR6v1/ur1LXizRvLpZxF+ifGwDA5dS3q8MyrBHE9ONK0aYtYpnNW+R5cfPm+dr0bOFZFgDCIX0bRYLy/cLmlKPNx4R5izclTSzjcOrPbdRwnzONHQ6XNN+S6x0VJr824RwBQCwq1y8oPDs4XXI/dhnGIiW0a9BQBylqu0149gQAr1vur5ZwH5SeZQGIcz6n4VlW6g8AYBPuC7aIIeK9Q3/eTesr4bCcFxUi3gtTbAD7mOvvB37DlIiIiIiIiIiIiKgWF0yJiIiIiIiIiIiIanHBlIiIiIiIiIiIiKgWF0yJiIiIiIiIiIiIanHBlIiIiIiIiIiIiKgWF0yJiIiIiIiIiIiIajka+sFINCLmhUMhbXp1TY1YJhZT2nSbZYllXC63Ic+lTU9PTxfLOD36Mi6nPh0AhGoDAOxOp75MTC4TFdq1olLfpgCwfsOvYl7JrhJtusOhrxsApKSkaNM3b9kiltmwbq2Yl5WVpU1v16atWKZd+w7adI9HXzcAsNnk9X6pG4WEvronLyjmbS/dri8TkLdXVV2lTU/3+cQymZn6tgOArl26adO3FMnnqahooza9oqJcLFPl19cbAGDpL4Dq6mqxSFZ2tjb9iK5HiGW83lQxr6ZGf55+WFEolrHZ9B3CMow3KakeMS9YHdCmV1Wbxjz9QLBzh75vAcAxvfuIeb40/diWZuhf4aC+vy77brlYpirgF/NiSn9MP6z4QSwTDYW16TanfDuy2+1iXnp6hja9VatWYhlL6Mem/gDIdQAMNwaxhFRG3papelIpcxk50xLObTQizwViSmhXe+PHagCwhDHesuTt2R1CGXk3xrOnhGMytp2wRWlbABBT8vZiUX25mIrKdRA2FzVNSCiJ6d5WWV2pTfcbykSUvn8GnPL8w+6Q575eYY5kd8r9yebUj2VpqWlimVhMvh/ahb4bCsn9MxzT55XtlucfG9avFvMCwlzMZmiHSmEetG3bTrFMVVWFmOfx6Octrdu0FsscecTh2nS72yuWcVjyM4p04YeFMQQAKirle3xION5glVzG79f3/8xsedzOztHPEwHA5dKX27lLPk/VAX0dtm6V58slpbvFPIl8HweaNc/VprcsaCGWSUuR577SOdxVskssU1SsH1dsLvm6cDjla728Qt+u/ir9nBgAXG7982fA0Ifs0M8TASAjXf+clCWkA0BpWak2ff0G+Vl269ZiMS8S1o9ToYD8DBAS1kRCEflY0zPkNYzU7BxtutMtPzc7HPqxXxkmYjbD/M0mzc0NiyXSNMhul+cmpud9aYMpHvm+adpcLKa/l0Qj8vO+U2g/p11+rlExuc3tdv0Y73HJ12YorL/Ww2G53hHD+GWz6c+tw2Got/AcFzHMVcNh+byHI/pyNsP823Cr2y/8hikRERERERERERFRLS6YEhEREREREREREdXigikRERERERERERFRLS6YEhEREREREREREdXigikRERERERERERFRLTl8116UEDEXAGqEyNABQ9S8dJ8+8tuunfoo74Ac3Q0AUrz6iJJSBFEAcLr0xxSxy1GAI4aon7aIfv3ZboiS5hKin24vkyNnL/j6GzGvSog6aDeEhHO59XUwRe6rESLAA8Cu3fpz6K+Uy1RW6OudmZkplsnK0UcIBACHELkvbDimstIyMW+3cEwVZXLE1IxMfR8PCVHCASA9Qx/xGwDatmmjTXe55Iipq9f8qE0vMUTVLCuTr0G3Wx+hr2VLOQrs4sULtek7dm4Tyxze9Qgx78S+/bTpGYa+IkWZrqiQz9/OnXIb7ajeqk2PGCKISxEHAzVyf1jz889innRtdO7SVSyza4f+mKToigAQCctj3oZ1G7TpLVrIUWBTUvRjtTMq92O7Vx7H3cL4ZQhILrJMIdsh3wOlYqbtycHKDdHXTRHlmxD83LQ9KQp8zBBlPSRE4/R45Xu3ZYgOLxdqfKbxWE2dRSinjNHm9YVMuzFFW5bqF4vK16a0vUhUHqMoWUVAnsdWVunnvuGI3DfsSh8x2iafSviry8S8QFA/djfPl6OOe1z6OlimPmiIehyKCsdrGv+UfkyoMETO/u775WLeDuHelpKqP9Y9efqI5DHDsZYb5omRmD6vxjDnswn3lR6GeV1OM/mYpKoHwvJ1X1Yiz/lKtuvnOm4hGjIAuIT+pQyRkr0eeXspXn308zZtmotlaqr0UdF37pCfraqq5GeU1FT9vKXCXymWWbP6F2160FCmZ4/Dxbx2nTtp07Mz5ejwNuESLPPLc9+KSvkarK6q1qa7HKb7of68l5XuFkv8+KMcbT5XiA7fplVbsUx1jf7chg2Rz2HJ40Dxti3a9ECNfL9IS9PPY6U5LABjOPcUt/46czhM34WT5iZNmasCUWE+YaqBXbgv2Az7Mc2lHXZhzmeYcIWE6OsAoIShMhaV6xARxniXXR6r7YZWkkp5nabt6Y/X0I2hpAECAGz6gsqSx+poTOhflvwM4E6Rn+8cwjN1JCjfz8KG59n9wW+YEhEREREREREREdXigikRERERERERERFRLS6YEhEREREREREREdXigikRERERERERERFRLS6YEhEREREREREREdXigikRERERERERERFRLUdDPxiNKjEvHI5o01M8KWKZjPRMbbplyVUqLy0R89JSfdp0l9splonF9MdUU1UjlolEomKeJCVVbgeny6VNz8zIFss0a9ZCzFu79ldtemVVhVjG8uvb3HAqEAmHxDyv26NNV9GYWCYUCmrTt23ZIu/H6xXzPEJeKCTXu6ZGPu9bNuvrIR0rAFRVVGrTq50Bscyu3dvFPJvw9w3Lkv/u0fuYY7XphauWi2UqKg19RajDlqJNYhlY+uS1a9eKRYo2bxbzNgv7Oubo3mKZI4/qqU0vKGgulmnVuqWYFw5306aX7i4Vy2zdWtzoMmXl5WJeMKDvyzUB/bUEAE6nfrwJh8NiGYfDLuZV11QLddCnA0CaTz9WwxI6CgDY5Ty7UD+l5HuWdD8zVQGG7UHpCxpKwG5vwt8rlaGMTX9vMtUhpuQxWayCoR0iEakfyWO1aXvS+VCGo5K21/gjjW9QrIQoGtPvLabk+YMl7QcQGyIUkq9bqUwk2vg5zP+yWFQe/xwp+vt/WpYwxgFId+uvBcsw+ESi8rzF7dLXL9Ulz00i1VXa9JDSpwNAzDKNf/o6pKSkikV8Wfo8h5UllinIyxHzgsIxVfn18zAAiIb116nlNNzzgvL91SWcQxWTr9Ndu3Zp07dv2yGWyc7NE/NsNv3EXX4SAmJR/TMcAJTt1j93ud36uQQAeIR5cU2NPPeNGYY/t/Acl+5LE8s0K2imTd+wdp1YZudOef7tEJ7VpL4PAJs36+d8kYD8rNG6pTzv7NVHv72eR/YQy/Tsqc9r176NWCYckvtDSan+etpZIs9Vi3fo+3KgWr6WAgH5mtkuXDN2m9yJqoW+FzMtgzjkqybg19e9xiPfX1PS9H3FshmuTsN9wRImITbDPMNl1+8rYpPnllFL7uORiL4dTHNLS6iDEtZk9rW9mDAvjgjPSHvKGOZOQlPYHXJfUULfM807Y4ZzGxXG5Fi1XywTFtrIYai33dDHldTmEfk8BaJCfzDcY8RFAgCW0PfChjlRSLiv7y9+w5SIiIiIiIiIiIioFhdMiYiIiIiIiIiIiGpxwZSIiIiIiIiIiIioFhdMiYiIiIiIiIiIiGpxwZSIiIiIiIiIiIioFhdMiYiIiIiIiIiIiGo5GvpBC5aY501J1aa7PG55x067Nr1582ZimWbN8sU8m6Vf+7U75EOsrKzQl7HL68jRWEzMg9In2236YwUAp0uflwK57bp16yZXQekrsbW4SCzjcrm06eV+ffsAAKLCwQI4rF0HbXpBq9ZimZU/rtSmVy1ZJJapClSJeeX+Sm36jh07xDJlpaViXvHWYm261O8AwLLrrxmHTe6TMRUV89J9Gdr0zMxMscyukl3a9PXr14plTNe6x+vVpjsN11koFNam1wRqxDLBUEjMW7Z8mTb9xx9/FMsc/v0SbXqf3n3EMod17CLm5eTkatPz8vPEMs1bNNemhw3HWlUl9/Gqan37lZfJ/dgS+qvNMOaVlu8W87Kzs7Xp+fktxDJu4b5gM/S7tNQ0MU+6BqWxcE8ZfZ6pTEwZxn6RfEw24b5gyUVgqB4A/fZihrFamY4pJrSRoQZS/SzDQRnPk9R+pmoL59bYroYNCpszHpMl3PJtSr7OYhG5DuGwfoyICucIABzC/cdmaAdK5vX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      "text/plain": [
       "<Figure size 1400x700 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Loading model from: ../models/model_ffp_channels_last_epochs50_normFalse_l0.001_cr3_20230308150355.h5\n",
      "Bitrate shape: (1,)\n"
     ]
    },
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 1400x700 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Loading model from: ../models/model_ffp_channels_last_epochs50_normFalse_l0.01_cr3_20230308164627.h5\n",
      "Bitrate shape: (1,)\n"
     ]
    },
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 1400x700 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Loading model from: ../models/model_ffp_channels_last_epochs50_normFalse_l0.1_cr3_20230308182410.h5\n",
      "Bitrate shape: (1,)\n"
     ]
    },
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 1400x700 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "for model_path in models_path:\n",
    "    print(\"Loading model from: {}\".format(model_path))\n",
    "    vae.load_weights(model_path)\n",
    "    img_reco, rate_reco = vae(img, training=False) # type: ignore\n",
    "    \n",
    "    compressor = Compressor(vae, COD_RANK)\n",
    "    \n",
    "\n",
    "    for i in range(img.shape[0]):\n",
    "        bits_reco = show_image_comparison_bitrate(img[i], img_reco[i], ids[i], CH_FORMAT, compressor)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Compression ratio"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Original bit rate: 221184\n"
     ]
    }
   ],
   "source": [
    "# compute the bitrates for the original images\n",
    "original_bit_rate = np.product(img[0].shape)*8\n",
    "\n",
    "print(\"Original bit rate: {}\".format(original_bit_rate))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [],
   "source": [
    "def bitrate_onbatch(img, compressor):\n",
    "    \n",
    "    if type(img) == np.ndarray:\n",
    "        img = tf.constant(img)\n",
    "        \n",
    "    bits = compressor(img)[1]\n",
    "    \n",
    "    bit_mean = tf.math.reduce_mean(bits)\n",
    "    bit_std  = tf.math.reduce_std(bits)\n",
    "    \n",
    "    return bit_mean, bit_std"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Loading model from: ../models/model_ffp_channels_last_epochs50_normFalse_l1e-05_cr3_20230308115252.h5\n",
      "Bitrate: 88938.45 +/- 542.91 bits/pixel\n",
      "Loading model from: ../models/model_ffp_channels_last_epochs50_normFalse_l0.0001_cr3_20230308132810.h5\n",
      "Bitrate: 87764.15 +/- 399.10 bits/pixel\n",
      "Loading model from: ../models/model_ffp_channels_last_epochs50_normFalse_l0.001_cr3_20230308150355.h5\n",
      "Bitrate: 85589.91 +/- 77.61 bits/pixel\n",
      "Loading model from: ../models/model_ffp_channels_last_epochs50_normFalse_l0.01_cr3_20230308164627.h5\n",
      "Bitrate: 82849.65 +/- 30.56 bits/pixel\n",
      "Loading model from: ../models/model_ffp_channels_last_epochs50_normFalse_l0.1_cr3_20230308182410.h5\n",
      "Bitrate: 84159.15 +/- 6.88 bits/pixel\n"
     ]
    }
   ],
   "source": [
    "n_images = 1000\n",
    "\n",
    "img, ids = select_random_images(data, n_images)\n",
    "\n",
    "bit_rates_mean_list = []\n",
    "bit_rates_err_list  = []\n",
    "\n",
    "for model_path in models_path:\n",
    "    print(\"Loading model from: {}\".format(model_path))\n",
    "    vae.load_weights(model_path)\n",
    "    img_reco, rate_reco = vae(img, training=False) # type: ignore\n",
    "    \n",
    "    compressor = Compressor(vae, COD_RANK)\n",
    "\n",
    "    bit_rates_mean, bit_rates_std = bitrate_onbatch(img_reco, compressor)\n",
    "    \n",
    "    print(f\"Bitrate: {bit_rates_mean.numpy():.2f} +/- {bit_rates_std.numpy():.2f} bits/pixel\")\n",
    "    \n",
    "    bit_rates_mean_list.append(bit_rates_mean)\n",
    "    bit_rates_err_list.append(bit_rates_std)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 800x500 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# plot the bitrates comparing the original image with the reconstructed images\n",
    "\n",
    "compression_ratio = original_bit_rate / np.array(bit_rates_mean_list)\n",
    "compression_ratio_err = compression_ratio * np.array(bit_rates_err_list) / np.array(bit_rates_mean_list)\n",
    "\n",
    "\n",
    "fig, ax = plt.subplots(figsize=(8, 5), constrained_layout=True)\n",
    "ax.grid(True, which='both', ls='-', lw=0.5, c='grey', alpha=0.3)\n",
    "\n",
    "ax.errorbar(\n",
    "    x          = lambdas, \n",
    "    y          = compression_ratio, \n",
    "    yerr       = compression_ratio_err, \n",
    "    ls         = \"--\", \n",
    "    lw         = 1, \n",
    "    marker     = \"o\", \n",
    "    markersize = 8, \n",
    "    color      = \"k\",\n",
    "    # elinewidth = 2,\n",
    "    # capsize    = 5,\n",
    "    # capthick   = 2,\n",
    ")\n",
    "\n",
    "ax.set_xscale('log')\n",
    "\n",
    "ax.set_xlabel(\"$\\lambda$\")\n",
    "ax.set_ylabel(\"Compression ratio (CR = $\\dfrac{B_{original}}{B_{reco}}$)\")\n",
    "\n",
    "fig.savefig(\"./plots/compression_ratio_cr3_lambda_scan_uwu.png\", dpi=300, facecolor=\"w\")\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## PSNR / MS-SIM"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Loading model from: ../models/model_ffp_channels_last_epochs50_normFalse_l1e-05_cr3_20230308115252.h5\n",
      "PSNR: 23.27 +/- 2.77\n",
      "MS-SSIM: 0.9591 +/- 0.0338\n",
      "Loading model from: ../models/model_ffp_channels_last_epochs50_normFalse_l0.0001_cr3_20230308132810.h5\n",
      "PSNR: 23.24 +/- 2.76\n",
      "MS-SSIM: 0.9575 +/- 0.0349\n",
      "Loading model from: ../models/model_ffp_channels_last_epochs50_normFalse_l0.001_cr3_20230308150355.h5\n",
      "PSNR: 23.08 +/- 2.66\n",
      "MS-SSIM: 0.9479 +/- 0.0417\n",
      "Loading model from: ../models/model_ffp_channels_last_epochs50_normFalse_l0.01_cr3_20230308164627.h5\n",
      "PSNR: 21.14 +/- 1.82\n",
      "MS-SSIM: 0.8728 +/- 0.0684\n",
      "Loading model from: ../models/model_ffp_channels_last_epochs50_normFalse_l0.1_cr3_20230308182410.h5\n",
      "PSNR: 15.09 +/- 1.71\n",
      "MS-SSIM: 0.5494 +/- 0.1045\n"
     ]
    }
   ],
   "source": [
    "n_images = 1000\n",
    "\n",
    "img, ids = select_random_images(data, n_images)\n",
    "\n",
    "psnr_mean_list = []\n",
    "psnr_err_list  = []\n",
    "\n",
    "mssim_mean_list = []\n",
    "mssim_err_list  = []\n",
    "\n",
    "for model_path in models_path:\n",
    "    print(\"Loading model from: {}\".format(model_path))\n",
    "    vae.load_weights(model_path)\n",
    "    img_reco, rate_reco = vae(img, training=False) # type: ignore\n",
    "    \n",
    "    psnr_mean, psnr_err = psnr_onbatch(img, img_reco)\n",
    "    \n",
    "    psnr_mean_list.append(psnr_mean)\n",
    "    psnr_err_list.append(psnr_err)   \n",
    "    \n",
    "    mssim_mean, mssim_err = msssim_onbatch(img, img_reco, CH_FORMAT, NORM) \n",
    "    \n",
    "    mssim_mean_list.append(mssim_mean)\n",
    "    mssim_err_list.append(mssim_err)\n",
    "    \n",
    "    print(\"PSNR: {:.2f} +/- {:.2f}\".format(psnr_mean, psnr_err))\n",
    "    print(\"MS-SSIM: {:.4f} +/- {:.4f}\".format(mssim_mean, mssim_err))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 800x500 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# plot the PSNR comparing the original image with the reconstructed images\n",
    "\n",
    "fig, ax = plt.subplots(figsize=(8, 5), constrained_layout=True)\n",
    "ax.grid(True, which='both', ls='-', lw=0.5, c='grey', alpha=0.3)\n",
    "\n",
    "ax.errorbar(\n",
    "    x          = lambdas, \n",
    "    y          = psnr_mean_list, \n",
    "    yerr       = psnr_err_list, \n",
    "    ls         = \"--\", \n",
    "    lw         = 1, \n",
    "    marker     = \"o\", \n",
    "    markersize = 8, \n",
    "    color      = \"k\",\n",
    "    elinewidth = 2,\n",
    "    capsize    = 5,\n",
    "    capthick   = 2,\n",
    ")\n",
    "\n",
    "ax.set_xscale('log')\n",
    "\n",
    "\n",
    "ax.set_xlabel(\"$\\lambda$\")\n",
    "ax.set_ylabel(\"PSNR (dB)\")\n",
    "\n",
    "fig.savefig(\"./plots/psnr_cr3_lambda_scan_uwu.png\", dpi=300, facecolor=\"w\")\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 800x500 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# plot the MSSIM comparing the original image with the reconstructed images\n",
    "\n",
    "fig, ax = plt.subplots(figsize=(8, 5), constrained_layout=True)\n",
    "ax.grid(True, which='both', ls='-', lw=0.5, c='grey', alpha=0.3)\n",
    "\n",
    "ax.errorbar(\n",
    "    x          = lambdas, \n",
    "    y          = mssim_mean_list, \n",
    "    yerr       = mssim_err_list, \n",
    "    ls         = \"--\", \n",
    "    lw         = 1, \n",
    "    marker     = \"o\", \n",
    "    markersize = 8, \n",
    "    color      = \"k\",\n",
    "    elinewidth = 2,\n",
    "    capsize    = 5,\n",
    "    capthick   = 2,\n",
    ")\n",
    "\n",
    "ax.set_xscale('log')\n",
    "\n",
    "\n",
    "ax.set_xlabel(\"$\\lambda$\")\n",
    "ax.set_ylabel(\"MS-SSIM\")\n",
    "\n",
    "fig.savefig(\"./plots/mssim_cr3_lambda_scan_uwu.png\", dpi=300, facecolor=\"w\")\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Mutual Information"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [],
   "source": [
    "def mi_diffsize_onbatch(image1, image2):\n",
    "    # Convert images to grayscale\n",
    "    image1 = tf.reduce_mean(image1, axis=[1, 2, 3])\n",
    "    image2 = tf.reduce_mean(image2, axis=[1, 2, 3])\n",
    "\n",
    "    # Compute marginal histograms\n",
    "    hist1, _ = np.histogram(image1, bins='auto')\n",
    "    hist2, _ = np.histogram(image2, bins='auto')\n",
    "\n",
    "    # Compute joint histogram\n",
    "    joint_histogram, _, _ = np.histogram2d(image1, image2, bins=[hist1.shape[0], hist2.shape[0]])\n",
    "\n",
    "    # Normalize joint histogram\n",
    "    pxy = joint_histogram / np.sum(joint_histogram)\n",
    "\n",
    "\n",
    "    # Normalize marginal histograms\n",
    "    px = hist1 / np.sum(hist1)\n",
    "    py = hist2 / np.sum(hist2)\n",
    "\n",
    "    px_py = px[:, None] * py[None, :]\n",
    "\n",
    "    # Compute mutual information\n",
    "\n",
    "    nzrs_msk = (pxy > 0) & (px_py > 0)\n",
    "\n",
    "    return np.sum(pxy[nzrs_msk]*np.log2(pxy[nzrs_msk] / px_py[nzrs_msk]))\n",
    "\n",
    "\n",
    "def mi_ed(images):\n",
    "    # Convert images to grayscale\n",
    "    image1 = tf.reduce_mean(images[0], axis=-1).reshape((-1))\n",
    "    image2 = tf.reduce_mean(images[1], axis=-1).reshape((-1))\n",
    "\n",
    "    # Compute marginal histograms\n",
    "    hist1, _ = np.histogram(image1, bins='auto')\n",
    "    hist2, _ = np.histogram(image2, bins='auto')\n",
    "\n",
    "    # Compute joint histogram\n",
    "    joint_histogram, _, _ = np.histogram2d(image1, image2, bins=[hist1.shape[0], hist2.shape[0]])\n",
    "\n",
    "    # Normalize joint histogram\n",
    "    pxy = joint_histogram / np.sum(joint_histogram)\n",
    "\n",
    "\n",
    "    # Normalize marginal histograms\n",
    "    px = hist1 / np.sum(hist1)\n",
    "    py = hist2 / np.sum(hist2)\n",
    "\n",
    "    px_py = px[:, None] * py[None, :]\n",
    "\n",
    "    # Compute mutual information\n",
    "\n",
    "    nzrs_msk = (pxy > 0) & (px_py > 0)\n",
    "\n",
    "    return tf.reduce_sum(pxy[nzrs_msk]*np.log2(pxy[nzrs_msk] / px_py[nzrs_msk]))\n",
    "\n",
    "def mi_samesize_onbatch(image1, image2):\n",
    "    MIs = tf.map_fn(mi_ed, (image1, image2), dtype=(tf.float32, tf.float32), fn_output_signature=tf.float64).numpy()\n",
    "    return MIs.mean(), MIs.std()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Loading model from: ../models/model_ffp_channels_last_epochs50_normFalse_l1e-05_cr3_20230308115252.h5\n",
      "MI original/encoded: 0.4364613486674986\n",
      "MI encoded/decoded : 2.3041833179473032 +- 0.21845704949599076\n",
      "MI original/reco   : 2.5278905621151564 +- 0.33295674095534067\n",
      "Loading model from: ../models/model_ffp_channels_last_epochs50_normFalse_l0.0001_cr3_20230308132810.h5\n",
      "MI original/encoded: 0.5467310336211713\n",
      "MI encoded/decoded : 2.2092412088710827 +- 0.20426787965388166\n",
      "MI original/reco   : 2.4884009072191637 +- 0.33421838865783066\n",
      "Loading model from: ../models/model_ffp_channels_last_epochs50_normFalse_l0.001_cr3_20230308150355.h5\n",
      "MI original/encoded: 0.42845658557182026\n",
      "MI encoded/decoded : 1.7325582519017972 +- 0.19661390354190447\n",
      "MI original/reco   : 2.3872555736439343 +- 0.3129946258272005\n",
      "Loading model from: ../models/model_ffp_channels_last_epochs50_normFalse_l0.01_cr3_20230308164627.h5\n",
      "MI original/encoded: 0.9384419475798054\n",
      "MI encoded/decoded : 1.0241863551013 +- 0.23973338448091955\n",
      "MI original/reco   : 1.7794824529832112 +- 0.28217493947520333\n",
      "Loading model from: ../models/model_ffp_channels_last_epochs50_normFalse_l0.1_cr3_20230308182410.h5\n",
      "MI original/encoded: 1.0249067046050837\n",
      "MI encoded/decoded : 0.829201343381201 +- 0.27259677323237824\n",
      "MI original/reco   : 1.033693881212885 +- 0.2720536797378187\n"
     ]
    }
   ],
   "source": [
    "n_images = 1000\n",
    "\n",
    "img, ids = select_random_images(data, n_images)\n",
    "\n",
    "mi_oe_list = []\n",
    "mi_ed_list = []\n",
    "mi_ed_err_list = []\n",
    "mi_or_list = []\n",
    "mi_or_err_list = []\n",
    "\n",
    "for model_path in models_path:\n",
    "    print(\"Loading model from: {}\".format(model_path))\n",
    "    vae.load_weights(model_path)\n",
    "    img_reco, rate_reco = vae(img, training=False) # type: ignore\n",
    "\n",
    "    compressor   = Compressor(vae, COD_RANK)\n",
    "    decompressor = Decompressor(vae, COD_RANK)\n",
    "\n",
    "    img_enc = vae.encoder(img, training=False)\n",
    "\n",
    "    img_bitstrings = compressor(img)[0]\n",
    "    img_decoded    = decompressor(img_bitstrings)\n",
    "\n",
    "    mi_oe_list.append(mi_diffsize_onbatch(img, img_enc))\n",
    "    mi_ed_mean, mi_ed_std = mi_samesize_onbatch(img_enc, img_decoded)\n",
    "    mi_ed_list.append(mi_ed_mean)\n",
    "    mi_ed_err_list.append(mi_ed_std)\n",
    "    mi_or_mean, mi_or_std = mi_samesize_onbatch(img, img_reco)\n",
    "    mi_or_list.append(mi_or_mean)\n",
    "    mi_or_err_list.append(mi_or_std)\n",
    "\n",
    "    print(f'MI original/encoded: {mi_oe_list[-1]}')\n",
    "    print(f'MI encoded/decoded : {mi_ed_list[-1]} +- {mi_ed_err_list[-1]}')\n",
    "    print(f'MI original/reco   : {mi_or_list[-1]} +- {mi_or_err_list[-1]}')\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 800x500 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# plot the MSSIM comparing the original image with the reconstructed images\n",
    "\n",
    "fig, ax = plt.subplots(figsize=(8, 5), constrained_layout=True)\n",
    "ax.grid(True, which='both', ls='-', lw=0.5, c='grey', alpha=0.3)\n",
    "\n",
    "ax.plot(\n",
    "    lambdas, \n",
    "    mi_oe_list, \n",
    "    ls         = \"--\", \n",
    "    lw         = 1, \n",
    "    marker     = \"o\", \n",
    "    markersize = 8, \n",
    "    color      = \"k\",\n",
    ")\n",
    "\n",
    "ax.set_xscale('log')\n",
    "\n",
    "\n",
    "ax.set_xlabel(\"$\\lambda$\")\n",
    "ax.set_ylabel(\"MI Original/Encoded\")\n",
    "\n",
    "fig.savefig(\"./plots/mioe_cr3_lambda_scan.png\", dpi=300, facecolor=\"w\")\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 800x500 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots(figsize=(8, 5), constrained_layout=True)\n",
    "ax.grid(True, which='both', ls='-', lw=0.5, c='grey', alpha=0.3)\n",
    "\n",
    "ax.errorbar(\n",
    "    x          = lambdas, \n",
    "    y          = mi_ed_list, \n",
    "    yerr       = mi_ed_err_list, \n",
    "    ls         = \"--\", \n",
    "    lw         = 1, \n",
    "    marker     = \"o\", \n",
    "    markersize = 8, \n",
    "    color      = \"k\",\n",
    "    elinewidth = 2,\n",
    "    capsize    = 5,\n",
    "    capthick   = 2,\n",
    ")\n",
    "\n",
    "ax.set_xscale('log')\n",
    "\n",
    "\n",
    "ax.set_xlabel(\"$\\lambda$\")\n",
    "ax.set_ylabel(\"MI Encoded/Decoded\")\n",
    "\n",
    "fig.savefig(\"./plots/mied_cr3_lambda_scan.png\", dpi=300, facecolor=\"w\")\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 800x500 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots(figsize=(8, 5), constrained_layout=True)\n",
    "ax.grid(True, which='both', ls='-', lw=0.5, c='grey', alpha=0.3)\n",
    "\n",
    "ax.errorbar(\n",
    "    x          = lambdas, \n",
    "    y          = mi_or_list, \n",
    "    yerr       = mi_or_err_list, \n",
    "    ls         = \"--\", \n",
    "    lw         = 1, \n",
    "    marker     = \"o\", \n",
    "    markersize = 8, \n",
    "    color      = \"k\",\n",
    "    elinewidth = 2,\n",
    "    capsize    = 5,\n",
    "    capthick   = 2,\n",
    ")\n",
    "\n",
    "ax.set_xscale('log')\n",
    "\n",
    "\n",
    "ax.set_xlabel(\"$\\lambda$\")\n",
    "ax.set_ylabel(\"MI Original/Reconstructed\")\n",
    "\n",
    "fig.savefig(\"./plots/mior_cr3_lambda_scan.png\", dpi=300, facecolor=\"w\")\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "tf2",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.9.16"
  },
  "orig_nbformat": 4
 },
 "nbformat": 4,
 "nbformat_minor": 2
}
